diff --git a/docs/404.html b/docs/404.html index 4004561..0e7a4d6 100644 --- a/docs/404.html +++ b/docs/404.html @@ -1,66 +1,27 @@ - - - - + + + + - Page not found (404) • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + - - - - -
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Page not found (404)

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Page not found (404)

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-
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-
- -
- -
+

License

@@ -169,31 +106,27 @@

License

+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/articles/analysis.html b/docs/articles/analysis.html index 148ed6e..d6658fd 100644 --- a/docs/articles/analysis.html +++ b/docs/articles/analysis.html @@ -19,6 +19,8 @@ + +
+

Analyzing inForm data

-

Kent Johnson

+

Kent Johnson

-

2021-08-18

+

2022-01-03

- Source: vignettes/analysis.Rmd + Source: vignettes/analysis.Rmd
-
-

-Analysis overview

+
+

Analysis overview +

A phenoptrReports analysis aggregates cell phenotypes and marker expression for each slide and tissue category in an experiment. An analysis can aggregate phenoype counts, density, mean expression and H-Score.

There are three parts to creating an analysis:

    @@ -124,35 +126,35 @@

  • define the desired analysis
  • create the final reports

-
-

-Data requirements

-
-

-Consolidated cell seg data

+
+

Data requirements +

+
+

Consolidated cell seg data +

The primary source data for the analysis report is a consolidated data file created by the Consolidate and summarize app.

If you have only one merge file, from a single inForm project, you should still use Consolidate and summarize to convert the file to the format used by the analysis report.

-
-

-Other files

+
+

Other files +

Two other input files are optional.

If provided, phenotprReports will use a merged cell seg summary file to compute tissue area and cell density within tissue categories. A score data summary file is used to compute H-Score per slide and tissue category.

-
-

-Detailed steps

-
-

-Start the analysis app

+
+

Detailed steps +

+
+

Start the analysis app +

Choose “Analyze consolidated data” from the RStudio Addins menu to open the analysis app.

-
-

-Select input files

+
+

Select input files +

The first tab in the analysis app is Files. Use this tab to select the input files and output directory for your analysis.

  1. First, click the first Browse… button to select the consolidated data file created in the consolidation app. This is the most important input file and the only one that is required.

    2. @@ -162,26 +164,26 @@

-
-

-Define the analysis

+
+

Define the analysis +

The second tab in the analysis app is Analysis. It contains sections where you select tissue categories, phenotypes, and markers of interest.

-
-

-Tissue categories

+
+

Tissue categories +

In this section, select the tissue categories to include in the analysis.

-
-

-Slide ID prefix

-

The Slide IDs in your data file may contain prefix information that is not wanted in the final report. Any text you enter here will be removed from the start of the Slide IDs. The text can be either an exact match or a regular expression. Exact matches will match from the start of the Slide ID. Regular expressions will match anywhere in the Slide ID; to match only from the start, start the regular expression with ^.

+
+

Slide ID prefix +

+

The Slide IDs in your data file may contain prefix information that is not wanted in the final report. Any text you enter here will be removed from the start of the Slide IDs. The text can be either an exact match or a regular expression. Exact matches will match from the start of the Slide ID. Regular expressions will match anywhere in the Slide ID; to match only from the start, start the regular expression with ^.

Leave this field blank to use the existing Slide IDs unchanged.

-
-

-Define phenotypes and markers

+
+

Define phenotypes and markers +

In this section you define the phenotypes and markers of interest. Every phenotype defined in this section will be included in the Cell Counts, Cell Percents and Cell Density sections of the final report. Phenotypes for which you select an expression marker will also be included in the Mean Expression section of the report.

The available phenotypes are shown at the top of the section. These are the phenotype names you can use in your phenotype definitions.

In the “Phenotype” box, enter the definition of a phenotype of interest. You can enter a single or multiple phenotype.

@@ -192,15 +194,15 @@

-
-

-H-Score for individual phenotypes

+
+

H-Score for individual phenotypes +

If you selected a score summary file in the Files tab, the phenotype selections will include a “Score” checkbox. If this is checked, the generated report will include H-Score for the selected phenotype in addition to the H-Score for all cells.

-
-

-Select options for spatial analysis

+
+

Select options for spatial analysis +

In this section, select the types of spatial analysis to include.

  • Include nearest neighbor summary If this is selected, the generated report will include a table summarizing nearest neighbor distances between every pair of phenotypes and heatmap visualizations of the mean distances.

    • @@ -216,9 +218,9 @@

-
-

-Create reports

+
+

Create reports +

The final tab in the analysis app is the Run tab. Click “Create Report” to run the displayed R script to create the final reports. Wait for the script to run; when it is finished, the app will close.

The script computes aggregated statistics, writes them to an Excel workbook, and creates visualizations of the results in a Word document. The R script is saved in the output directory and may be inspected, modified or re-run if needed.

@@ -237,11 +239,13 @@

-

Developed by Kent S Johnson, Akoya Biosciences.

+

+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown 2.0.1.

@@ -250,5 +254,7 @@

+ + diff --git a/docs/articles/component_levels_report.html b/docs/articles/component_levels_report.html index 9545d7d..e61b328 100644 --- a/docs/articles/component_levels_report.html +++ b/docs/articles/component_levels_report.html @@ -19,6 +19,8 @@ + +
+

Component levels report

-

Kent Johnson

+

Kent Johnson

-

2021-08-18

+

2022-01-03

- Source: vignettes/component_levels_report.Rmd + Source: vignettes/component_levels_report.Rmd
@@ -115,43 +117,43 @@

2021-08-18

The component levels report analyzes unmixed, multiplex images to help evaluate staining and unmixing quality. This report shows the relative strength of each component and crosstalk between components.

-
-

-Data requirements

+
+

Data requirements +

The input to this report is an inForm export directory containing multiplex images which have been unmixed by inForm using a candidate spectral library.

Multiplex images are taken from slides stained with a multiple fluorophores and a counterstain. The export directory should contain component data files from one or more images in the experiment.

-
-

-Detailed steps

-
-

-Choose “Component levels report” from the RStudio Addins menu

+
+

Detailed steps +

+
+

Choose “Component levels report” from the RStudio Addins menu +

This will open the component levels report app.

Image showing RStudio Addin menu

-
-

-Select input files

+
+

Select input files +

Click the “Browse” button in the “Select Export directory” section of the GUI. Use the directory selection dialog to select the directory containing exported component data files.

Image highlighting the Browse button

-
-

-Enter the quantiles of interest

+
+

Enter the quantiles of interest +

The component levels report shows the pixel intensity of each fluor in each image. Selected quantiles are shown with black bars and exported in CSV files. Enter the fractions corresponding to the quantiles of interest. The default value, 0.99, will show the signal level that is greater than 99% of the pixels in each image. This is a reasonable measure of peak signal intensity.

Enter the desired quantiles in the text field. Multiple values can be entered, separated by comma or space.

Image showing the entry field for desired quantiles

-
-

-Select export option

+
+

Select export option +

The component levels report includes “pairs plots” showing the expression levels of each component against each other component. These can help identify problematic crosstalk. Check the box “Export data from pairs plots” to have the report include text files containing the raw data for the plots.

Image showing Export data checkbox

-
-

-Create report

+
+

Create report +

Click “Create Report” to begin generating the report. The app will create an HTML file containing the analysis results and and two CSV files containing values from the report.

Image showing Create Report button

@@ -169,11 +171,13 @@

-

Developed by Kent S Johnson, Akoya Biosciences.

+

+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown 2.0.1.

@@ -182,5 +186,7 @@

+ + diff --git a/docs/articles/consolidation.html b/docs/articles/consolidation.html index 0f52494..0003796 100644 --- a/docs/articles/consolidation.html +++ b/docs/articles/consolidation.html @@ -19,6 +19,8 @@ + +
+

Consolidating inForm data

-

Kent Johnson

+

Kent Johnson

-

2021-08-18

+

2022-01-03

- Source: vignettes/consolidation.Rmd + Source: vignettes/consolidation.Rmd
-
-

-Data consolidation overview

+
+

Data consolidation overview +

The first step in a phenoptrReports data analysis is data consolidation.

The consolidation step combines the output from multiple inForm projects into a single consolidated data file and creates columns for each individual phenotype. The inputs to this step are merged cell seg data files from multiple inForm projects. The output is a consolidated data file and a summary report for each file.

NOTE: The consolidation step will fail if the Slide IDs and Cell IDs in the merge files do not exactly agree. This can happen, for example, if

@@ -127,58 +129,58 @@

Run the consolidation step even if your data comes from a single inForm project. This creates a data file in the format that the analysis step uses.

-
-

-Data requirements

-
-

-Merged cell seg data

+
+

Data requirements +

+
+

Merged cell seg data +

The primary source data for phenoptrReports is one or more merged cell seg data files created in the inForm Review/Merge tab. You may use multiple merge files from multiple inForm projects with different phenotypes. The Slide ID and Cell ID fields in multiple merge files must agree exactly.

-
-

-Tissue segmentation

+
+

Tissue segmentation +

inForm projects used with phenoptrReports must include a tissue segmentation step.

-
-

-Phenotypes

+
+

Phenotypes +

The names of positive phenotypes used with phenoptrReports must end with “+”, for example “CD8+” or “FoxP3+”. Negative and “Other” phenotype names should not end in “+”.

-
-

-Detailed steps

-
-

-Choose “Consolidate and summarize” from the RStudio Addins menu

+
+

Detailed steps +

+
+

Choose “Consolidate and summarize” from the RStudio Addins menu +

Thus will open the consolidation app.

-
-

-Select source files

+
+

Select source files +

Click the “Browse Input” button in the “Select source data files” section of the GUI. Use the file selection dialog to select your inForm merge data files. If the files are in multiple directories, click the Browse button multiple times to select them.

Select “Keep only phenoptrReports fields” to reduce the size of the consolidated data file by omitting rarely used fields such as Min and Max expression and cell Compactness.

-
-

-Select output directory

+
+

Select output directory +

Click the “Browse Output” button in the “Select output directory” section of the GUI. Use the directory selection dialog to create a new directory to contain the output files.

-
-

-Process files

+
+

Process files +

Click the “Process Files” button to start processing of the selected files.

A small progress meter will open to show progress. Any errors will be shown in the RStudio Console pane.

-
-

-View summary reports

+
+

View summary reports +

When processing completes, the output directory will contain several files:

  • @@ -194,9 +196,9 @@

  • visualizations of the combination phenotypes present in the data

-
-

-Next: Analysis

+
+

Next: Analysis +

Continue to the next tutorial to learn how to complete your analysis.

@@ -213,11 +215,13 @@

-

Developed by Kent S Johnson, Akoya Biosciences.

+

+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown 2.0.1.

@@ -226,5 +230,7 @@

+ + diff --git a/docs/articles/index.html b/docs/articles/index.html index b85fae6..c303a5f 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -1,66 +1,12 @@ - - - - - - - -Articles • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Articles • phenoptrReports - - + + - - -
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Articles

@@ -149,43 +86,39 @@

Articles

Tutorials

-
-
Consolidating inForm data
-
-
Analyzing inForm data
-
-
Viewing nearest neighbors
-
-
Unmixing quality report
-
-
Component levels report
-
-
Mean of top 20 / bottom 10 cells report
-
-
Staining consistency report
-
-
-
+
Consolidating inForm data
+
+
Analyzing inForm data
+
+
Viewing nearest neighbors
+
+
Unmixing quality report
+
+
Component levels report
+
+
Mean of top 20 / bottom 10 cells report
+
+
Staining consistency report
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/articles/spatial_map_viewer.html b/docs/articles/spatial_map_viewer.html index ad6e64b..fe97000 100644 --- a/docs/articles/spatial_map_viewer.html +++ b/docs/articles/spatial_map_viewer.html @@ -19,6 +19,8 @@ + +
+

Viewing nearest neighbors

-

Kent Johnson

+

Kent Johnson

-

2021-08-18

+

2022-01-03

- Source: vignettes/spatial_map_viewer.Rmd + Source: vignettes/spatial_map_viewer.Rmd
-
-

-Overview

+
+

Overview +

The “Spatial map viewer” addin allows viewing of nearest neighbor and touching relationships between cells of selected phenotypes in a single field. Views can be saved for later use.

-
-

-Data requirements

-
-

-Consolidated data file

+
+

Data requirements +

+
+

Consolidated data file +

This addin reads data from the Consolidated_data.txt file created by the “Consolidate and summarize” addin. It can also use the nearest_neighbors.txt or count_within.txt file created by the “Analyze consolidated data” addin when “Save nearest neighbor / count within details” is selected.

-
-

-Composite and component image files

+
+

Composite and component image files +

The viewer uses both composite and component image files for the fields of interest. These files are written by the inForm export step.

The composite images are shown as the background of the nearest neighbor visualizations. The colors and components shown are determined by the inForm export settings.

The component images are the source of metadata about fields that is needed to properly places cells in the visualizations.

-
-

-Segmentation image files

+
+

Segmentation image files +

Visualization of touching cells requires the binary_seg_map.tiff file created by an adaptive cell segmentation step in inForm.

-
-

-Detailed steps

-
-

-Start the spatial map viewer

+
+

Detailed steps +

+
+

Start the spatial map viewer +

Choose “Spatial map viewer” from the RStudio Addins menu to start the viewer.

-
-

-Select input files

+
+

Select input files +

The viewer’s initial screen allows you to select the nearest neighbor file and inForm export directory containing the fields of interest.

  1. First, click the “Browse input” button and select a Consolidated_data.txt file from the “Consolidate and summarize” addin or a nearest_neighbors.txt or count_within.txt file created by the analysis addin.

    2. @@ -159,9 +161,9 @@

-
-

-Nearest neighbor viewer

+
+

Nearest neighbor viewer +

The nearest neighbor viewer allows you to

  1. Select and color phenotypes In this section, select the two phenotypes of interest and the colors to use to display the phenotypes. Both single phenotypes such as CD8+ and multiple phenotypes such as CD8+/PDL1+ are supported.

    2. @@ -178,9 +180,9 @@

-
-

-Format of saved data files

+
+

Format of saved data files +

If “Save data with image” is selected, a tab-separated data file is saved with the image(s). The data file contains one row for each pair of connected cells, i.e. the cells that are connected with a white line segment in the images.

  • If “Save image” is clicked, the file will include data for the single image.
    • @@ -207,11 +209,13 @@

    -

    Developed by Kent S Johnson, Akoya Biosciences.

    +

    +

    Developed by Kent S Johnson, Akoya Biosciences.

    -

    Site built with pkgdown 1.6.1.

    +

    +

    Site built with pkgdown 2.0.1.

    @@ -220,5 +224,7 @@

    + + diff --git a/docs/articles/staining_consistency_report.html b/docs/articles/staining_consistency_report.html index 9ae1abf..1adbd61 100644 --- a/docs/articles/staining_consistency_report.html +++ b/docs/articles/staining_consistency_report.html @@ -19,6 +19,8 @@ + +
    +

    Staining consistency report

    -

    Kent Johnson

    +

    Kent Johnson

    -

    2021-08-18

    +

    2022-01-03

    - Source:     vignettes/staining_consistency_report.Rmd + Source: vignettes/staining_consistency_report.Rmd
    @@ -117,51 +119,51 @@

    2021-08-18

    The staining consistency report measures variation in the mean expression of a single marker across multiple images. It is used to assess consistency of staining within or across staining runs.

    When analyzing slides from a single staining run, this report can highlight inconsistent staining and suggest that autostainer maintenance is needed.

    When analyzing slides from multiple runs of an assay, the report can indicate changes in assay performance over time.

    -
    -

    -Data requirements

    +
    +

    Data requirements +

    The input to this report is a merged cell seg data file from inForm containing data about the samples to measure.

    -
    -

    -Detailed steps

    -
    -

    -Choose “Staining consistency report” from the RStudio Addins menu

    +
    +

    Detailed steps +

    +
    +

    Choose “Staining consistency report” from the RStudio Addins menu +

    This will open the app.

    Image showing RStudio Addin menu

    -
    -

    -Select merge file

    +
    +

    Select merge file +

    Click the “Browse” button in the “Select Merge Data” section of the GUI. Use the file selection dialog to select the file containing your merge data.

    Image highlighting the Browse button

    -
    -

    -Select marker and compartment

    +
    +

    Select marker and compartment +

    Select the marker and cell compartment for the report from the drop-down menus.

    Image showing selection of marker and compartment

    -
    -

    -Create report

    +
    +

    Create report +

    Click “Create Report” to begin generating the report. The app will create an HTML document with the results.

    Image showing Create Report button

    -
    -

    -Guidance

    -
    -

    -Good result

    +
    +

    Guidance +

    +
    +

    Good result +

    In general, a good result will have a relatively narrow range of mean values, limited outliers beyond the ±1 SD range, and a CV less than 15%.

    Image showing good results

    -
    -

    -Problem indications

    +
    +

    Problem indications +

    A wide range of mean values, outliers far outside the ±1 SD range, or CV greater than 15% indicates a possible problem.

    If the slides are from a single staining run, the autostainer may need maintenance.

    If the slides are from multiple runs, the variation may be due to one of these causes:

    @@ -188,11 +190,13 @@

    -

    Developed by Kent S Johnson, Akoya Biosciences.

    +

    +

    Developed by Kent S Johnson, Akoya Biosciences.

    -

    Site built with pkgdown 1.6.1.

    +

    +

    Site built with pkgdown 2.0.1.

    @@ -201,5 +205,7 @@

    + + diff --git a/docs/articles/top_20_bottom_10_report.html b/docs/articles/top_20_bottom_10_report.html index 6b812eb..142448d 100644 --- a/docs/articles/top_20_bottom_10_report.html +++ b/docs/articles/top_20_bottom_10_report.html @@ -19,6 +19,8 @@ + +
    +

    Mean of top 20 / bottom 10 cells report

    -

    Kent Johnson

    +

    Kent Johnson

    -

    2021-08-18

    +

    2022-01-03

    - Source:     vignettes/top_20_bottom_10_report.Rmd + Source: vignettes/top_20_bottom_10_report.Rmd
    -
    -

    -Introduction

    +
    +

    Introduction +

    The “Mean of Top 20/ bottom 10” analysis is performed on multiplexed fluorescent IHC images. The analysis helps to evaluate whether the staining quality is likely to produce good unmixing of the markers in the image. The analysis computes the mean expression of selected markers in the 20 highest-expressing cells and the 10% lowest-expressing cells. The resulting Excel workbook has tabs showing

    • @@ -131,13 +133,13 @@

      Generally, the best unmixing results are obtained when the expression levels of all fluors (excluding DAPI) are within the range of 10-30 normalized counts. Most importantly, the ratio between neighboring fluors should fall between 0.3-3 for multispectral IM3 images or 0.1-10 for MOTiF images. When one fluor is 3x/10x (IM3/MOTiF) brighter than its neighboring fluor, unmixing error and crosstalk are more likely to occur.

      The signal-to-background value helps to assess background levels in relation to real, positive signal. When higher background is present, resulting in a lower signal-to-background ratio, cell scoring based on thresholding will be less reliable and will likely result in more false positives. Phenotyping may also be more challenging. The app is will flag signal-to-background values of 30 or less within the Opal 780 channel as this fluor tends to have lower intensities with higher background levels.

    -
    -

    -Data requirements

    +
    +

    Data requirements +

    The input to this report is a merged cell seg data file from inForm containing data about the samples to measure, and a configuration file naming the markers of interest.

    -
    -

    -Configuration file

    +
    +

    Configuration file +

    The configuration file is a plain text file (.txt). It contains the names of the columns to measure, one name per line, without the units information. For example, a configuration file might have these contents:

    Nucleus DAPI Mean
 Membrane CD8 (Opal 480) Mean
@@ -149,52 +151,52 @@ 
    
 
    The order of entries in the configuration file determines which markers will be compared as adjacent markers in the report.
    -
    -

    -Detailed steps

    -
    -

    -Choose “Mean of top 20 / bottom 10 cells” from the RStudio Addins menu

    +
    +

    Detailed steps +

    +
    +

    Choose “Mean of top 20 / bottom 10 cells” from the RStudio Addins menu +

    This will open the app.

    Image showing RStudio Addin menu

    -
    -

    -Select merge file

    +
    +

    Select merge file +

    Click the “Browse” button in the “Select Merge Data” section of the GUI. Use the file selection dialog to select the file containing your merge data.

    Image highlighting the first Browse button

    -
    -

    -Select merge file options

    +
    +

    Select merge file options +

    If the merge file contains tissue category data, select the tissue categories to analyze.

    Image showing tissue category selection

    You can report by slide or by field. Make the appropriate selection in the “Summarize by” drop-down.

    Image showing Summarize by selection

    -
    -

    -Select a configuration file

    +
    +

    Select a configuration file +

    Click the “Browse” button

    Image highlighting the second Browse button

    -
    -

    -Set the ratio limit

    +
    +

    Set the ratio limit +

    Set the desired maximum ration of high expression in adjacent fluors. Ratios larger than this will be highlighted in the generated report.

    Recommended values are 10 for MOTiF images and 3 for multispectral IM3 images.

    Image of numeric entry field for maximum ratio

    -
    -

    -Create report

    +
    +

    Create report +

    Click “Create Report” to begin generating the report. The app will create an Excel workbook with the numerical analysis results and a Word document with charts which visualize the results.

    Image showing Create Report button

    -
    -

    -Guidelines

    +
    +

    Guidelines +

    This table gives some general guidelines for interpreting the results.

    @@ -252,11 +254,13 @@

    -

    Developed by Kent S Johnson, Akoya Biosciences.

    +

    +

    Developed by Kent S Johnson, Akoya Biosciences.

    -

    Site built with pkgdown 1.6.1.

    +

    +

    Site built with pkgdown 2.0.1.

    @@ -265,5 +269,7 @@

    + + diff --git a/docs/articles/unmixing_quality_report.html b/docs/articles/unmixing_quality_report.html index 1f0c445..5ce4a4b 100644 --- a/docs/articles/unmixing_quality_report.html +++ b/docs/articles/unmixing_quality_report.html @@ -19,6 +19,8 @@ + +
    +

    Unmixing quality report

    -

    Kent Johnson

    +

    Kent Johnson

    -

    2021-08-18

    +

    2022-01-03

    - Source:     vignettes/unmixing_quality_report.Rmd + Source: vignettes/unmixing_quality_report.Rmd
    @@ -115,38 +117,38 @@

    2021-08-18

    The unmixing quality report analyzes unmixed, singleplex images to help evaluate staining and unmixing quality. This report shows crosstalk between components and highlights potential problem areas in assay development.

    -
    -

    -Data requirements

    +
    +

    Data requirements +

    The input to this report is an inForm export directory containing singleplex images which have been unmixed by inForm using a candidate spectral library.

    Singleplex images are taken from slides stained with a single fluorophore and no counterstain (except on the DAPI singleplex). The export directory should contain component data files from one or more images for each fluor in the experiment.

    The report generator must identify the Opal fluor for each source file by looking at the file name. It recognizes names containing “DAPI”, “AF”, “Opalnnn” and “Opal_nnn”. It also recognizes three leading digits as the number of an Opal fluor.

    -
    -

    -Detailed steps

    -
    -

    -Choose “Unmixing quality report” from the RStudio Addins menu

    +
    +

    Detailed steps +

    +
    +

    Choose “Unmixing quality report” from the RStudio Addins menu +

    This will open the quality reporting app.

    -
    -

    -Select input files

    +
    +

    Select input files +

    Click the “Browse” button in the “Select Export directory” section of the GUI. Use the directory selection dialog to select the directory containing exported component data files.

    -
    -

    -Create report

    +
    +

    Create report +

    Click the “Create Report” button to start processing of the selected directory.

    When the report is complete, the app window will close. Any errors will be reported in the RStudio Console pane.

    -
    -

    -View the report

    +
    +

    View the report +

    When processing completes, the export directory will contain a file Unmixing_quality_report.html which may be viewed in any web browser.

    @@ -163,11 +165,13 @@

    -

    Developed by Kent S Johnson, Akoya Biosciences.

    +

    +

    Developed by Kent S Johnson, Akoya Biosciences.

    -

    Site built with pkgdown 1.6.1.

    +

    +

    Site built with pkgdown 2.0.1.

    @@ -176,5 +180,7 @@

    + + diff --git a/docs/authors.html b/docs/authors.html index 488dc8d..6c29646 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -1,66 +1,12 @@ - - - - - - - -Authors • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Authors and Citation • phenoptrReports - - + + - - - -
    -
    -
    - -
    +
    -
    -

    Authors

    +
    +
    +

    Authors

    +
    + + +
    • +

      Kent S Johnson. Author, maintainer. +

      +
      • +
    • +

      Carla Coltharp. Contributor. +

      +
      • +
    • +

      Akoya Biosciences. Copyright holder, funder. +

      +
      • +
    +
    +
    +

    Citation

    + Source: DESCRIPTION +
    -
      -
    • -

      Kent S Johnson. Author, maintainer. -

      -
      • -
    • -

      Carla Coltharp. Contributor. -

      -
      • -
    • -

      Akoya Biosciences. Copyright holder, funder. -

      -
      • -
    + +

    Johnson K (2022). +phenoptrReports: Create reports using Phenoptics data. +https://akoyabio.github.io/phenoptrReports/, +https://github.com/akoyabio/phenoptrReports/. +

    + 
    @Manual{,
+  title = {phenoptrReports: Create reports using Phenoptics data},
+  author = {Kent S Johnson},
+  year = {2022},
+  note = {https://akoyabio.github.io/phenoptrReports/,
+https://github.com/akoyabio/phenoptrReports/},
+}
    @@ -166,22 +124,20 @@

    Authors

    -
    -
    -

    Developed by Kent S Johnson, Akoya Biosciences.

    +
    +

    Developed by Kent S Johnson, Akoya Biosciences.

    -

    Site built with pkgdown 1.6.1.

    +

    Site built with pkgdown 2.0.1.

    -
    -
    +
    - - + + diff --git a/docs/index.html b/docs/index.html index a24759a..c00d7eb 100644 --- a/docs/index.html +++ b/docs/index.html @@ -19,6 +19,8 @@ + +
    -
    -

    -phenoptrReports +
    +

    phenoptrReports

    -
    -

    -Reports and visualizations from inForm data

    +
    +

    Reports and visualizations from inForm data +

    phenoptrReports generates reports and visualizations based on data created by Akoya Biosciences’ inForm® software.

    -

    phenoptrReports is part of the Akoya Biosciences Phenoptics™ family of Quantitative Pathology Research Solutions. For more information visit the Phenoptics™ home page.

    +

    phenoptrReports is part of the Akoya Biosciences Phenoptics™ family of Quantitative Pathology Research Solutions. For more information visit the Phenoptics™ home page.

    -
    -

    -Installation

    -

    The analysis apps in phenoptrReports run as “Addins” to the RStudio IDE, which must also be installed.

    -

    phenoptrReports uses the Akoya Biosciences phenoptr package for much of its functionality. Please follow the phenoptr installation instructions, including the optional installations, before installing phenoptrReports.

    +
    +

    Installation +

    +

    The analysis apps in phenoptrReports run as “Addins” to the RStudio IDE, which must also be installed.

    +

    phenoptrReports uses the Akoya Biosciences phenoptr package for much of its functionality. Please follow the phenoptr installation instructions, including the optional installations, before installing phenoptrReports.

    Next, install phenoptrReports from GitHub. In the RStudio console, copy and paste or type this command:

    -
    remotes::install_github("akoyabio/phenoptrReports")
    +
    remotes::install_github("akoyabio/phenoptrReports")
    -
    -

    -Getting Started

    +
    +

    Getting Started +

    phenoptrReports functionality is provided via RStudio Addins. These are small applications accessed via the “Addins” menu in the RStudio IDE.

    -
    -

    -Merge data from individual fields

    +
    +

    Merge data from individual fields +

    The Merge cell seg files addin merges inForm data files from individual fields to create “Merge” data files. This is similar to the inForm Merge tab but does not include the ability to review and reject individual fields. Use this addin if you are not able to merge in inForm for any reason.

    This addin allows you to select an inForm export directory containing data files for individual fields. It creates merge data files combining data for all fields.

    -
    -

    -Consolidate merged data to a single file

    +
    +

    Consolidate merged data to a single file +

    The Consolidate and summarize addin combines the output from multiple inForm projects into a single consolidated data file, creating columns for each individual phenotype. The inputs to this addin are merged cell seg data files created by inForm. The output is a consolidated data file and a summary report for each file.

    Run the consolidation addin even if your data comes from a single inForm project. This creates a data file in the format that the analysis addin uses.

    -

    For detailed instructions and requirements, see the Consolidating inForm data tutorial.

    +

    For detailed instructions and requirements, see the Consolidating inForm data tutorial.

    -
    -

    -Data analysis

    +
    +

    Data analysis +

    The Analyze consolidated data addin reads data produced by the consolidation addin. It aggregates phenoype counts, density, mean expression and H-Score for each slide and tissue category in an experiment and can also report on nearest neighbors and count cells within a radius.

    This addin creates

      @@ -158,40 +159,40 @@

      The most important input file is the consolidated data file from the consolidation addin. Selecting a summary cell seg data file enables density calculations; selecting a score data file enables H-Score calculation.

      To define the analysis, you select tissue categories, phenotypes, and markers of interest.

      To create the final reports, the analysis app writes and runs an R script. The script computes the aggregated statistics, writes them to an Excel workbook, and creates visualizations of the results in a Word document.

      -

      For detailed instructions and requirements, see the Analyzing inForm data tutorial.

      +

      For detailed instructions and requirements, see the Analyzing inForm data tutorial.

    -
    -

    -Visualization of spatial relationships

    +
    +

    Visualization of spatial relationships +

    The Spatial map viewer addin creates visualizations of nearest neighbors of selected phenotypes within individual fields. The visualizations can be saved for use in other applications.

    The spatial map viewer requires a Consolidated_data.txt file from the consolidation app or the nearest_neighbors.csv file created by the analysis addin, and an inForm image directory containing composite and component images.

    -

    For detailed instructions and requirements, see the Visualizing spatial relationships tutorial.

    +

    For detailed instructions and requirements, see the Visualizing spatial relationships tutorial.

    -
    -

    -Unmixing quality report

    +
    +

    Unmixing quality report +

    The Unmixing quality report addin analyzes unmixed, singleplex images to help evaluate staining and unmixing quality. This report shows crosstalk between components and highlights potential problem areas in assay development.

    -

    For more information about the unmixing quality report, see the Unmixing quality report tutorial.

    +

    For more information about the unmixing quality report, see the Unmixing quality report tutorial.

    -
    -

    -Component levels report

    +
    +

    Component levels report +

    The Component levels report addin analyzes unmixed, multiplex images to help evaluate staining levels for an entire experiment. This report shows the distribution of signal and dark pixels for all components.

    -

    For more information about the component levels report, see the Component levels report tutorial.

    +

    For more information about the component levels report, see the Component levels report tutorial.

    -
    -

    -Mean of Top 20/ bottom 10 report

    +
    +

    Mean of Top 20/ bottom 10 report +

    The Mean of Top 20/ bottom 10 analysis helps to evaluate whether the staining quality is likely to produce good unmixing of the markers in the image. The analysis computes the mean expression of selected markers in the 20 highest-expressing cells and the 10% lowest-expressing cells.

    -

    For detailed instructions and requirements, see the Mean of top 20 / bottom 10 cells tutorial.

    +

    For detailed instructions and requirements, see the Mean of top 20 / bottom 10 cells tutorial.

    -
    -

    -Staining consistency report

    +
    +

    Staining consistency report +

    The Staining consistency report measures variation in the mean expression of a single marker across multiple images. It is used to assess consistency of staining across multiple staining runs.

    -

    For detailed instructions and requirements, see the Staining consistency report tutorial.

    +

    For detailed instructions and requirements, see the Staining consistency report tutorial.

    -

    R-CMD-check

    +
    @@ -199,28 +200,43 @@

    - - - - - - - - - -
    caption

    Caption for the choose directory dialog

    default

    Starting directory

    - -

    Value

    +
    + 
    choose_directory(caption = "Select folder", default = "")
    +
    +
    +

    Arguments

    +
    caption
    +

    Caption for the choose directory dialog

    +
    default
    +

    Starting directory

    +
    +
    +

    Value

    The path to the selected directory, or NA if the user canceled.

    +
    +
    -
    -
    -

    Developed by Kent S Johnson, Akoya Biosciences.

    +
    +

    Developed by Kent S Johnson, Akoya Biosciences.

    -

    Site built with pkgdown 1.6.1.

    +

    Site built with pkgdown 2.0.1.

    -
    -
    +
    - - + + diff --git a/docs/reference/choose_files.html b/docs/reference/choose_files.html index 8f987d1..1bb3f4b 100644 --- a/docs/reference/choose_files.html +++ b/docs/reference/choose_files.html @@ -1,67 +1,12 @@ - - - - - - - -Cross-platform choose files function — choose_files • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Cross-platform choose files function — choose_files • phenoptrReports + + - - - - -
    -
    -

- - -
+

Cross-platform choose files function

- Source: R/utilities.R + Source: R/utilities.R
@@ -152,64 +88,53 @@

Cross-platform choose files function

Cross-platform choose files function

- 
choose_files(
-  caption = "Select files",
-  default = "",
-  multi = TRUE,
-  filters = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
caption

Caption for the choose directory dialog

default

Starting directory

multi

Allow multiple files to be selected

filters

A two-column matrix of filename filters, or a two-element -vector containing a single filter.

- -

Value

+
+ 
choose_files(
+  caption = "Select files",
+  default = "",
+  multi = TRUE,
+  filters = NULL
+)
+
+
+

Arguments

+
caption
+

Caption for the choose directory dialog

+
default
+

Starting directory

+
multi
+

Allow multiple files to be selected

+
filters
+

A two-column matrix of filename filters, or a two-element +vector containing a single filter.

+
+
+

Value

The path to the selected file(s), or NA if the user canceled.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/component_levels_report.html b/docs/reference/component_levels_report.html index 9940a8f..b69a0e0 100644 --- a/docs/reference/component_levels_report.html +++ b/docs/reference/component_levels_report.html @@ -1,70 +1,15 @@ - - - - - - - -Create a component levels report for multiplex samples — component_levels_report • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create a component levels report for multiplex samples — component_levels_report • phenoptrReports - - - - - - - - - + + - - - - -
-
- -
- -
+

Create a component levels report for multiplex samples

- Source: R/reports.R + Source: R/reports.R
@@ -158,62 +94,53 @@

Create a component levels report for multiplex samples

the source directory.

- 
component_levels_report(
-  export_path = NULL,
-  quantiles = 0.999,
-  export_data = FALSE
-)
- -

Arguments

- - - - - - - - - - - - - - -
export_path

Path to a directory containing component_data files.

quantiles

Quantiles to show in the histograms and use for -signal-to-noise calculations.

export_data

If true, save a data file for each pairs plot with -the data for the plot.

- -

Details

+
+ 
component_levels_report(
+  export_path = NULL,
+  quantiles = 0.999,
+  export_data = FALSE
+)
+
+
+

Arguments

+
export_path
+

Path to a directory containing component_data files.

+
quantiles
+

Quantiles to show in the histograms and use for +signal-to-noise calculations.

+
export_data
+

If true, save a data file for each pairs plot with +the data for the plot.

+
+
+

Details

If two or more quantiles are provided, the report will include an signal-to-noise table showing the ratio of the highest quantile to the lowest.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_density_from_cell_summary.html b/docs/reference/compute_density_from_cell_summary.html index ceb6073..4ef22bc 100644 --- a/docs/reference/compute_density_from_cell_summary.html +++ b/docs/reference/compute_density_from_cell_summary.html @@ -1,68 +1,13 @@ - - - - - - - -Compute cell densities from counts and tissue area — compute_density_from_cell_summary • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute cell densities from counts and tissue area — compute_density_from_cell_summary • phenoptrReports - + + - - - -
-
- -
- -
+

Compute cell densities from counts and tissue area

- Source: R/compute_density.R + Source: R/compute_density.R
@@ -154,83 +90,71 @@

Compute cell densities from counts and tissue area

read from a summary cell seg data file.

- 
compute_density_from_cell_summary(
-  counts,
-  summary_path,
-  tissue_categories,
-  pixels_per_micron = getOption("phenoptr.pixels.per.micron"),
-  .by = "Slide ID"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
counts

A data frame with columns for .by, Tissue Category, -and counts, such as the output of count_phenotypes.

summary_path

Path(s) to cell seg data summary table(s) containing -sample names and tissue categories matching counts.

tissue_categories

A character vector of tissue category names -of interest.

pixels_per_micron

Conversion factor to microns.

.by

Column to aggregate by

- -

Value

+
+ 
compute_density_from_cell_summary(
+  counts,
+  summary_path,
+  tissue_categories,
+  pixels_per_micron = getOption("phenoptr.pixels.per.micron"),
+  .by = "Slide ID"
+)
+
+
+

Arguments

+
counts
+

A data frame with columns for .by, Tissue Category, +and counts, such as the output of count_phenotypes.

+
summary_path
+

Path(s) to cell seg data summary table(s) containing +sample names and tissue categories matching counts.

+
tissue_categories
+

A character vector of tissue category names +of interest.

+
pixels_per_micron
+

Conversion factor to microns.

+
.by
+

Column to aggregate by

+
+
+

Value

A data table with counts converted to density in \(cells / mm^2\).

-

See also

- -

Other aggregation functions: -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity_many(), -compute_positivity(), -count_phenotypes(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_density_from_table.html b/docs/reference/compute_density_from_table.html index f720a20..542289b 100644 --- a/docs/reference/compute_density_from_table.html +++ b/docs/reference/compute_density_from_table.html @@ -1,68 +1,13 @@ - - - - - - - -Compute cell densities from counts and tissue area — compute_density_from_table • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute cell densities from counts and tissue area — compute_density_from_table • phenoptrReports - - + + - - -
-
- -
- -
+

Compute cell densities from counts and tissue area

- Source: R/compute_density.R + Source: R/compute_density.R
@@ -154,74 +90,64 @@

Compute cell densities from counts and tissue area

a table of tissue areas.

- 
compute_density_from_table(counts, areas, tissue_categories, .by = "Slide ID")
- -

Arguments

- - - - - - - - - - - - - - - - - - -
counts

A data frame with columns for .by, Tissue Category, -and counts, such as the output of count_phenotypes.

areas

A data frame containing tissue areas -in \(cells / micron^2\) with -sample names and tissue categories matching counts.

tissue_categories

A character vector of tissue category names -of interest.

.by

Column to aggregate by

- -

Value

+
+ 
compute_density_from_table(counts, areas, tissue_categories, .by = "Slide ID")
+
+
+

Arguments

+
counts
+

A data frame with columns for .by, Tissue Category, +and counts, such as the output of count_phenotypes.

+
areas
+

A data frame containing tissue areas +in \(cells / micron^2\) with +sample names and tissue categories matching counts.

+
tissue_categories
+

A character vector of tissue category names +of interest.

+
.by
+

Column to aggregate by

+
+
+

Value

A data table with counts converted to density in \(cells / mm^2\).

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity_many(), -compute_positivity(), -count_phenotypes(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_h_score.html b/docs/reference/compute_h_score.html index 18ebb17..6bdcfe2 100644 --- a/docs/reference/compute_h_score.html +++ b/docs/reference/compute_h_score.html @@ -1,67 +1,12 @@ - - - - - - - -Compute H-Score for a single marker aggregated by .by — compute_h_score • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute H-Score for a single marker aggregated by .by — compute_h_score • phenoptrReports - + + - - - -
-
- -
- -
+

Compute H-Score for a single marker aggregated by .by

- Source: R/positivity.R + Source: R/positivity.R
@@ -152,77 +88,65 @@

Compute H-Score for a single marker aggregated by .by

Parameters are directly provided.

- 
compute_h_score(csd, measure, tissue_categories, thresholds, .by = "Slide ID")
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
csd

Cell seg data to use.

measure

The cell seg data column to measure (as a character string)

tissue_categories

A character vector of tissue category names -of interest.

thresholds

Optional three element vector with the threshold values.

.by

Column to aggregate by

- -

Value

+
+ 
compute_h_score(csd, measure, tissue_categories, thresholds, .by = "Slide ID")
+
+
+

Arguments

+
csd
+

Cell seg data to use.

+
measure
+

The cell seg data column to measure (as a character string)

+
tissue_categories
+

A character vector of tissue category names +of interest.

+
thresholds
+

Optional three element vector with the threshold values.

+
.by
+

Column to aggregate by

+
+
+

Value

A data frame with one row per Slide ID, showing cell counts and percents in each bin and the H-Score. The data frame has attributes measure and thresholds.

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity_many(), -compute_positivity(), -count_phenotypes(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_h_score_from_score_data.html b/docs/reference/compute_h_score_from_score_data.html index fc5db99..4fadaa6 100644 --- a/docs/reference/compute_h_score_from_score_data.html +++ b/docs/reference/compute_h_score_from_score_data.html @@ -1,67 +1,12 @@ - - - - - - - -Compute H-Score based on parameters in a score data file — compute_h_score_from_score_data • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute H-Score based on parameters in a score data file — compute_h_score_from_score_data • phenoptrReports - + + - - - -
-
- -
- -
+

Compute H-Score based on parameters in a score data file

- Source: R/positivity.R + Source: R/positivity.R
@@ -152,82 +88,70 @@

Compute H-Score based on parameters in a score data file

Compute H-Score based on parameters in a score data file

- 
compute_h_score_from_score_data(
-  csd,
-  score_path,
-  tissue_categories = NULL,
-  .by = "Slide ID",
-  phenotype = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
csd

Cell seg data to use.

score_path

Path to to a score_data file (may be merged or not).

tissue_categories

optionally specify tissue categories of interest. -If not given, tissue categories are taken from the score file.

.by

Column to aggregate by

phenotype

Optional phenotype to subset csd.

- -

Value

+
+ 
compute_h_score_from_score_data(
+  csd,
+  score_path,
+  tissue_categories = NULL,
+  .by = "Slide ID",
+  phenotype = NULL
+)
+
+
+

Arguments

+
csd
+

Cell seg data to use.

+
score_path
+

Path to to a score_data file (may be merged or not).

+
tissue_categories
+

optionally specify tissue categories of interest. +If not given, tissue categories are taken from the score file.

+
.by
+

Column to aggregate by

+
phenotype
+

Optional phenotype to subset csd.

+
+
+

Value

A data frame with one row per Slide ID, showing cell counts and -percents in each bin and the H-Score. See compute_h_score.

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity_many(), -compute_positivity(), -count_phenotypes(), -counts_to_percents()

+percents in each bin and the H-Score. See compute_h_score.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_mean_expression.html b/docs/reference/compute_mean_expression.html index 1271f3f..935139f 100644 --- a/docs/reference/compute_mean_expression.html +++ b/docs/reference/compute_mean_expression.html @@ -1,69 +1,14 @@ - - - - - - - -Compute mean expression of cells for a single phenotype and marker. — compute_mean_expression • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute mean expression of cells for a single phenotype and marker. — compute_mean_expression • phenoptrReports - - - - - - - - - - - - - + + -
-
- -
- -
+

Compute mean expression of cells for a single phenotype and marker.

- Source: R/mean_expression.R + Source: R/mean_expression.R
@@ -156,81 +92,69 @@

Compute mean expression of cells for a single phenotype and marker.

Report the mean expression of the high-expressing cells.

- 
compute_mean_expression(csd, phenotype, param, percentile = NULL, count = NULL)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
csd

Cell seg data to use. This should already have been filtered -for the slides or fields of interest.

phenotype

A phenotype selector. This will be passed to -phenoptr::select_rows.

param

The parameter (column) to report, as a string.

percentile

The percentile cutoff for top-expressing cells. For +

+ 
compute_mean_expression(csd, phenotype, param, percentile = NULL, count = NULL)
+
+ +
+

Arguments

+
csd
+

Cell seg data to use. This should already have been filtered +for the slides or fields of interest.

+
phenotype
+

A phenotype selector. This will be passed to +phenoptr::select_rows.

+
param
+

The parameter (column) to report, as a string.

+
percentile
+

The percentile cutoff for top-expressing cells. For example, to measure the top quartile, the percentile is 0.75. Negative numbers will use low-expressing cells; to measure the bottom decile, -use a percentile of -0.1.

count

The number of top expressing cells to use. Only one of +use a percentile of -0.1.

+
count
+

The number of top expressing cells to use. Only one of percentile and count can be provided. If both are omitted, -the mean expression of all cells is returned.

- -

Value

- +the mean expression of all cells is returned.

+
+
+

Value

A data frame with columns for count and mean.

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression_many(), -compute_positivity_many(), -compute_positivity(), -count_phenotypes(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_mean_expression_many.html b/docs/reference/compute_mean_expression_many.html index 7d7c79c..fb1b87d 100644 --- a/docs/reference/compute_mean_expression_many.html +++ b/docs/reference/compute_mean_expression_many.html @@ -1,68 +1,13 @@ - - - - - - - -Compute mean expression of cells for multiple phenotypes and markers. — compute_mean_expression_many • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute mean expression of cells for multiple phenotypes and markers. — compute_mean_expression_many • phenoptrReports - - + + - - -
-
- -
- -
+

Compute mean expression of cells for multiple phenotypes and markers.

- Source: R/mean_expression.R + Source: R/mean_expression.R
@@ -154,64 +90,51 @@

Compute mean expression of cells for multiple phenotypes and markers.

report the mean expression of the given marker in the specified cells.

- 
compute_mean_expression_many(
-  csd,
-  phenotypes,
-  params,
-  tissue_categories = NULL,
-  percentile = NULL,
-  count = NULL,
-  .by = "Slide ID"
-)
+
+ 
compute_mean_expression_many(
+  csd,
+  phenotypes,
+  params,
+  tissue_categories = NULL,
+  percentile = NULL,
+  count = NULL,
+  .by = "Slide ID"
+)
+
-

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
csd

Cell seg data to use. This should already have been filtered +

+

Arguments

+
csd
+

Cell seg data to use. This should already have been filtered for the slides or fields of interest. It may already be nested by -!!.by and Tissue Category.

phenotypes

A named list of phenotype selectors -(see phenoptr::parse_phenotypes).

params

A named list matching phenotype names to -expression column names.

tissue_categories

Optional vector of tissue category names to include.

percentile

The percentile cutoff for top-expressing cells. For +!!.by and Tissue Category.

+
phenotypes
+

A named list of phenotype selectors +(see phenoptr::parse_phenotypes).

+
params
+

A named list matching phenotype names to +expression column names.

+
tissue_categories
+

Optional vector of tissue category names to include.

+
percentile
+

The percentile cutoff for top-expressing cells. For example, to measure the top quartile, the percentile is 0.75. Negative numbers will use low-expressing cells; to measure the bottom decile, -use a percentile of -0.1.

count

The number of top expressing cells to use. Only one of +use a percentile of -0.1.

+
count
+

The number of top expressing cells to use. Only one of percentile and count can be provided. If both are omitted, all cells matching the phenotype are used and the result is the -overall mean expression.

.by

Column to aggregate by

- -

Value

- +overall mean expression.

+
.by
+

Column to aggregate by

+
+
+

Value

A data frame with a column for mean for each param_pair.

-

Details

- +
+
+

Details

This is a very flexible function. If percentile and count are both omitted, it will compute the mean expression for all cells in the given phenotype. If either percentile or count is given, the mean @@ -224,44 +147,42 @@

Details the .by parameter.

To aggregate over all cells, include "Total Cells"=NA as one of the phenotypes.

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression(), -compute_positivity_many(), -compute_positivity(), -count_phenotypes(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_positivity.html b/docs/reference/compute_positivity.html index 45d1556..fab01a4 100644 --- a/docs/reference/compute_positivity.html +++ b/docs/reference/compute_positivity.html @@ -1,67 +1,12 @@ - - - - - - - -Compute positivity of a single phenotype — compute_positivity • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute positivity of a single phenotype — compute_positivity • phenoptrReports - + + - - - -
-
- -
- -
+

Compute positivity of a single phenotype

- Source: R/positivity.R + Source: R/positivity.R
@@ -152,72 +88,64 @@

Compute positivity of a single phenotype

Compute positivity of a single phenotype

- 
compute_positivity(csd, phenotype, positivity)
- -

Arguments

- - - - - - - - - - - - - - -
csd

Cell seg data to use. This should already have been filtered -for the slides or fields of interest.

phenotype

A phenotype selector. This will be passed to -select_rows.

positivity

A one-sided formula giving the positivity expression -to evaluate.

- -

Value

+
+ 
compute_positivity(csd, phenotype, positivity)
+
+
+

Arguments

+
csd
+

Cell seg data to use. This should already have been filtered +for the slides or fields of interest.

+
phenotype
+

A phenotype selector. This will be passed to +select_rows.

+
positivity
+

A one-sided formula giving the positivity expression +to evaluate.

+
+
+

Value

A data frame with columns for count (total number of cells of the given phenotype), positive (count of positive cells) and fraction (fraction of positive cells).

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity_many(), -count_phenotypes(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/compute_positivity_many.html b/docs/reference/compute_positivity_many.html index 4eeb325..eee36f2 100644 --- a/docs/reference/compute_positivity_many.html +++ b/docs/reference/compute_positivity_many.html @@ -1,67 +1,12 @@ - - - - - - - -Compute positivity of multiple phenotypes — compute_positivity_many • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute positivity of multiple phenotypes — compute_positivity_many • phenoptrReports - - - - + + -
-
- -
- -
+

Compute positivity of multiple phenotypes

- Source: R/positivity.R + Source: R/positivity.R
@@ -152,81 +88,71 @@

Compute positivity of multiple phenotypes

Compute positivity of multiple phenotypes

- 
compute_positivity_many(
-  csd,
-  phenotypes,
-  positivity_pairs,
-  tissue_categories = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
csd

Cell seg data to use. This should already have been filtered -for the slides or fields of interest.

phenotypes

A named list of phenotype selectors -(see phenoptr::parse_phenotypes).

positivity_pairs

A named list of pairs (lists) of phenotype names -and positivity expressions. The expressions must be one-sided formulas -such as ~`Membrane PDL1 (Opal 520) Mean`>pdl1_threshold.

tissue_categories

Optional vector of tissue category names to include.

- -

Value

+
+ 
compute_positivity_many(
+  csd,
+  phenotypes,
+  positivity_pairs,
+  tissue_categories = NULL
+)
+
+
+

Arguments

+
csd
+

Cell seg data to use. This should already have been filtered +for the slides or fields of interest.

+
phenotypes
+

A named list of phenotype selectors +(see phenoptr::parse_phenotypes).

+
positivity_pairs
+

A named list of pairs (lists) of phenotype names +and positivity expressions. The expressions must be one-sided formulas +such as ~`Membrane PDL1 (Opal 520) Mean`>pdl1_threshold.

+
tissue_categories
+

Optional vector of tissue category names to include.

+
+
+

Value

A data frame with columns for count, positive count, and percent for each element of positivity_pairs.

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity(), -count_phenotypes(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/consolidate_and_summarize_cell_seg_data.html b/docs/reference/consolidate_and_summarize_cell_seg_data.html index fda90ca..56087b6 100644 --- a/docs/reference/consolidate_and_summarize_cell_seg_data.html +++ b/docs/reference/consolidate_and_summarize_cell_seg_data.html @@ -1,71 +1,16 @@ - - - - - - - -Consolidate cell seg data files from parallel projects -and create summary reports — consolidate_and_summarize_cell_seg_data • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Consolidate cell seg data files from parallel projects +and create summary reports — consolidate_and_summarize_cell_seg_data • phenoptrReports - - - - - - - - - - + + - - - -
-
- -
- -
+

Consolidate cell seg data files from parallel projects and create summary reports

- Source: R/split_phenotypes.R + Source: R/split_phenotypes.R
@@ -159,73 +95,63 @@

Consolidate cell seg data files from parallel projects into a single file with separate columns for each phenotype.

- 
consolidate_and_summarize_cell_seg_data(
-  csd_files,
-  output_dir,
-  update_progress = NULL,
-  col_select = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
csd_files

A list or vector of paths to cell seg data files.

output_dir

Path to a directory where the results will be saved.

update_progress

Callback function which is called with progress.

col_select

Column selection for phenoptr::read_cell_seg_data()

- -

Value

+
+ 
consolidate_and_summarize_cell_seg_data(
+  csd_files,
+  output_dir,
+  update_progress = NULL,
+  col_select = NULL
+)
+
+
+

Arguments

+
csd_files
+

A list or vector of paths to cell seg data files.

+
output_dir
+

Path to a directory where the results will be saved.

+
update_progress
+

Callback function which is called with progress.

+
col_select
+

Column selection for phenoptr::read_cell_seg_data()

+
+
+

Value

A single data frame containing consolidated data and columns for each single phenotype, invisibly.

-

Details

- +
+
+

Details

Create a summary report for each source file and the consolidated data.

Write the consolidated data to Consolidated_data.txt in the output directory.

The individual files must all have exactly the same Sample Name or Annotation ID and Cell ID -columns. split_phenotypes is called to split the Phenotype columns.

+columns. split_phenotypes is called to split the Phenotype columns.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+

- - + + diff --git a/docs/reference/count_phenotypes.html b/docs/reference/count_phenotypes.html index 12157a4..638fd36 100644 --- a/docs/reference/count_phenotypes.html +++ b/docs/reference/count_phenotypes.html @@ -1,69 +1,14 @@ - - - - - - - -Count phenotypes per slide and tissue category — count_phenotypes • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Count phenotypes per slide and tissue category — count_phenotypes • phenoptrReports - - - - - - - - - - - + + - - -
-
- -
- -
+

Count phenotypes per slide and tissue category

- Source: R/count_phenotypes.R + Source: R/count_phenotypes.R
@@ -156,76 +92,66 @@

Count phenotypes per slide and tissue category

each Slide ID.

- 
count_phenotypes(csd, phenotypes, tissue_categories, .by = "Slide ID")
- -

Arguments

- - - - - - - - - - - - - - - - - - -
csd

Cell seg data to use. This should already have been filtered -for the slides or fields of interest.

phenotypes

A named list of phenotype selectors -(see phenoptr::parse_phenotypes). Results will be -reported in the same order as phenotypes are listed here. To include a -row total, phenotypes should contain a "Total" item.

tissue_categories

A character vector of tissue category names -of interest.

.by

Column to aggregate by

- -

Value

+
+ 
count_phenotypes(csd, phenotypes, tissue_categories, .by = "Slide ID")
+
+
+

Arguments

+
csd
+

Cell seg data to use. This should already have been filtered +for the slides or fields of interest.

+
phenotypes
+

A named list of phenotype selectors +(see phenoptr::parse_phenotypes). Results will be +reported in the same order as phenotypes are listed here. To include a +row total, phenotypes should contain a "Total" item.

+
tissue_categories
+

A character vector of tissue category names +of interest.

+
.by
+

Column to aggregate by

+
+
+

Value

A data frame with columns for Slide ID, Tissue Category, cell counts for each requested phenotype, and total cells.

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity_many(), -compute_positivity(), -counts_to_percents()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/count_within_summary.html b/docs/reference/count_within_summary.html index 64e72c7..14d227c 100644 --- a/docs/reference/count_within_summary.html +++ b/docs/reference/count_within_summary.html @@ -1,70 +1,15 @@ - - - - - - - -Summarize "count within" distances — count_within_summary • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Summarize "count within" distances — count_within_summary • phenoptrReports - - - - + + -
-
- -
- -
+

Summarize "count within" distances

- Source: R/distance_helpers.R + Source: R/distance_helpers.R

Computes summary "count within" statistics for each Slide ID in csd and each pair of phenotypes in phenotypes. -See phenoptr::count_within() for details of the counts and the +See phenoptr::count_within() for details of the counts and the summary calculation.

- 
count_within_summary(
-  csd,
-  radii,
-  phenotypes = NULL,
-  categories = NA,
-  details_path = NULL,
-  .by = "Slide ID",
-  extra_cols = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
csd

Cell seg data with Cell X Position, -Cell Y Position, field name and Phenotype columns.

radii

Vector of radii to search within.

phenotypes

Optional list of phenotypes to include. If omitted, -will use unique_phenotypes(csd). Counts are computed for all -pairs of phenotypes.

categories

Optional list of tissue categories to compute within. If -omitted or NA, all cells will be included.

details_path

If present, path to save tab-separated tables with -count within data for each cell.

.by

Column to aggregate by

extra_cols

The names of extra columns to include in the detailed -results.

- -

Value

+
+ 
count_within_summary(
+  csd,
+  radii,
+  phenotypes = NULL,
+  categories = NA,
+  details_path = NULL,
+  .by = "Slide ID",
+  extra_cols = NULL
+)
+
+
+

Arguments

+
csd
+

Cell seg data with Cell X Position, +Cell Y Position, field name and Phenotype columns.

+
radii
+

Vector of radii to search within.

+
phenotypes
+

Optional list of phenotypes to include. If omitted, +will use unique_phenotypes(csd). Counts are computed for all +pairs of phenotypes.

+
categories
+

Optional list of tissue categories to compute within. If +omitted or NA, all cells will be included.

+
details_path
+

If present, path to save tab-separated tables with +count within data for each cell.

+
.by
+

Column to aggregate by

+
extra_cols
+

The names of extra columns to include in the detailed +results.

+
+
+

Value

A data frame with summary statistics for each phenotype pair in each Slide ID.

-

Details

- +
+
+

Details

If details_path is provided, this will save a table with one row per cell and columns for each phenotype and radius giving the count of cells of that type within that distance.

@@ -220,32 +143,29 @@

Details the results will include all cells in csd. If categories does not include NA, the "All" tissue category will include only cells in the provided categories.

+

+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/counts_to_percents.html b/docs/reference/counts_to_percents.html index 4179e04..105b8cf 100644 --- a/docs/reference/counts_to_percents.html +++ b/docs/reference/counts_to_percents.html @@ -1,69 +1,14 @@ - - - - - - - -Convert a count table to fractional percents — counts_to_percents • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Convert a count table to fractional percents — counts_to_percents • phenoptrReports - - - - - - - - - - - + + - - -
-
- -
- -
+

Convert a count table to fractional percents

- Source: R/count_phenotypes.R + Source: R/count_phenotypes.R
-

Converts a table of counts, such as the output of count_phenotypes, +

Converts a table of counts, such as the output of count_phenotypes, to a table of fractional percents. Percents are computed row-wise, e.g. per tissue category.

- 
counts_to_percents(counts)
+
+ 
counts_to_percents(counts)
+
-

Arguments

- - - - - - -
counts

A table containing count data. All numeric columns are +

+

Arguments

+
counts
+

A table containing count data. All numeric columns are assumed to contain count data. The table must contain a -column whose name contains "Total" or "All".

- -

Value

- +column whose name contains "Total" or "All".

+
+
+

Value

A table containing percent values as decimal fractions.

-

See also

- -

Other aggregation functions: -compute_density_from_cell_summary(), -compute_density_from_table(), -compute_h_score_from_score_data(), -compute_h_score(), -compute_mean_expression_many(), -compute_mean_expression(), -compute_positivity_many(), -compute_positivity(), -count_phenotypes()

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/discrete_colors.html b/docs/reference/discrete_colors.html index 950b030..28db5b0 100644 --- a/docs/reference/discrete_colors.html +++ b/docs/reference/discrete_colors.html @@ -1,67 +1,12 @@ - - - - - - - -Create a discrete palette with n colors — discrete_colors • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create a discrete palette with n colors — discrete_colors • phenoptrReports - + + - - - -
-
- -
- -
+

Create a discrete palette with n colors

- Source: R/utilities.R + Source: R/utilities.R
@@ -152,46 +88,41 @@

Create a discrete palette with n colors

Create a discrete palette with n colors

- 
discrete_colors(n)
- -

Arguments

- - - - - - -
n

The number of colors needed

- -

Value

+
+ 
discrete_colors(n)
+
+
+

Arguments

+
n
+

The number of colors needed

+
+
+

Value

A color vector of length n

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/index.html b/docs/reference/index.html index d589b34..b42d88c 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -1,66 +1,12 @@ - - - - - - - -Function reference • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Function reference • phenoptrReports - - - - + + -
-
- -
- -
+

Reference

- - - - - - - - - - -
-

RStudio Addins

-

These functions are added to the RStudio Addins menu. Selecting one opens a GUI.

+ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
+

RStudio Addins

+

These functions are added to the RStudio Addins menu. Selecting one opens a GUI.

+

addin_10_merge()

Merge cell seg data files

+

addin_20_consolidate()

Consolidate and summarize cell seg data files

+

addin_30_analysis_app()

Run the Analysis app

+

addin_35_spatial_map_viewer()

Spatial map viewer addin

+

addin_40_unmixing_quality()

Generate an unmixing quality (crosstalk) report for a selected export folder.

+

addin_50_component_levels()

Generate a component levels report for a selected export folder.

+

addin_60_mean_of_top_and_bottom_cells()

Generate a "Mean of top and bottom cells" report for a selected merge data file and configuration file.

+

addin_70_staining_consistency_report()

Generate a "Staining consistency" report for a selected merge data file.

-

Merging and Consolidation

-

These functions implement the merge and consolidation apps.

+
+

Merging and Consolidation

+

These functions implement the merge and consolidation apps.

+

merge_cell_seg_files()

Merge inForm output from multiple fields.

+

consolidate_and_summarize_cell_seg_data()

Consolidate cell seg data files from parallel projects and create summary reports

-

Calculations

-

These functions perform the calculations for an analysis.

+
+

Calculations

+

These functions perform the calculations for an analysis.

+

compute_density_from_cell_summary()

Compute cell densities from counts and tissue area

+

compute_density_from_table()

Compute cell densities from counts and tissue area

+

compute_h_score()

Compute H-Score for a single marker aggregated by .by

+

compute_h_score_from_score_data()

Compute H-Score based on parameters in a score data file

+

compute_mean_expression()

Compute mean expression of cells for a single phenotype and marker.

+

compute_mean_expression_many()

Compute mean expression of cells for multiple phenotypes and markers.

+

compute_positivity()

Compute positivity of a single phenotype

+

compute_positivity_many()

Compute positivity of multiple phenotypes

+

counts_to_percents()

Convert a count table to fractional percents

+

count_phenotypes()

Count phenotypes per slide and tissue category

+

count_within_summary()

Summarize "count within" distances

+

nearest_neighbor_summary()

Summarize nearest neighbor distances

-

Mean of top and bottom cells

-

These functions implement the Mean of top 20 / bottom 10 cells report

+
+

Mean of top and bottom cells

+

These functions implement the Mean of top 20 / bottom 10 cells report

+

mean_of_top_and_bottom_cells_report()

Create reports showing mean expression of top and bottom cells

+

mean_of_top_and_bottom_cells()

Compute mean expression levels of the top and bottom expressing cells, per Slide ID or field. This creates a quality report.

+

write_mean_of_top_and_bottom_charts()

Create summary charts from the results of mean_of_top_and_bottom_cells

-

Data reporting - HTML

-

These functions write analysis results to HTML reports.

+
+

Data reporting - HTML

+

These functions write analysis results to HTML reports.

+

component_levels_report()

Create a component levels report for multiplex samples

+

staining_consistency_report()

Actually generate the staining consistency report

+

unmixing_quality_report()

Create an unmixing quality report for simplex samples

+

write_summary_report()

Create a summary report for a cell seg data file

-

Data reporting - Excel and Word

-

These functions write analysis results to Excel worksheets and Word documents.

+
+

Data reporting - Excel and Word

+

These functions write analysis results to Excel worksheets and Word documents.

+

write_counts_sheet()

Write a cell counts table to an Excel workbook

+

write_count_within_sheet()

Write a "count within" summary to an Excel workbook

+

write_density_sheet()

Write a density table to an Excel workbook

+

write_expression_sheet()

Write an expression table to an Excel workbook

+

write_h_score_sheet()

Write an H-Score table to an Excel workbook

+

write_nearest_neighbor_summary_sheet()

Write a nearest neighbor summary to an Excel workbook

+

write_percents_sheet()

Write a cell percent table to an Excel workbook

+

write_plot_sheet()

Write a plot to an Excel workbook

+

write_sheet()

Write a single sheet with formatting common to all sheets.

+

write_summary_charts()

Create summary charts from the results of an analysis

+

write_summary_sheet()

Write a summary table to an Excel workbook

-

Helper functions

+
+

Helper functions

+

choose_directory()

Cross-platform choose directory function.

+

choose_files()

Cross-platform choose files function

+

discrete_colors()

Create a discrete palette with n colors

+

nearest_neighbor_map()

Make a nearest neighbor map for a single field

+

order_by_slide_and_tissue_category()

Order a data frame by slide ID and tissue category, putting the categories in the given order and the "Total" category in the proper place.

+

spatial_map_viewer()

Run the spatial map viewer with the given data file and export directory.

+

split_phenotypes()

Split all phenotype columns

+

unmixing_quality_report()

Create an unmixing quality report for simplex samples

+

upset_plot()

Create an UpSet plot showing the phenotype combinations present in data.

+

write_session_info()

Write session info to a file

- +
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/mean_of_top_and_bottom_cells.html b/docs/reference/mean_of_top_and_bottom_cells.html index cdee8ca..002854d 100644 --- a/docs/reference/mean_of_top_and_bottom_cells.html +++ b/docs/reference/mean_of_top_and_bottom_cells.html @@ -1,70 +1,15 @@ - - - - - - - -Compute mean expression levels of the top and bottom expressing cells, -per Slide ID or field. This creates a quality report. — mean_of_top_and_bottom_cells • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Compute mean expression levels of the top and bottom expressing cells, +per Slide ID or field. This creates a quality report. — mean_of_top_and_bottom_cells • phenoptrReports + + - - - - -
-
- -
- -
+

Compute mean expression levels of the top and bottom expressing cells, per Slide ID or field. This creates a quality report.

- Source: R/mean_of_top_and_bottom_cells.R + Source: R/mean_of_top_and_bottom_cells.R
@@ -157,86 +93,67 @@

Compute mean expression levels of the top and bottom expressing cells, as csd_path.

- 
mean_of_top_and_bottom_cells(
-  csd_path = NULL,
-  expression_cols,
-  top_count = 20,
-  bottom_percentile = 0.1,
-  adjacent_max = 3,
-  tissue_categories = NULL,
-  .by = "Slide ID",
-  out_path = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
csd_path

Path to a merged cell seg data, or NULL. If NULL, a file -chooser is opened to allow file selection.

expression_cols

Vector of column names to report.

top_count

The number of top-expressing cells to select for -averaging.

bottom_percentile

The cutoff for the bottom percentile cells.

adjacent_max

The maximum ratio between expression of adjacent fluors

tissue_categories

Tissue categories to include, or NULL for all

.by

The column to aggregate by

out_path

The path to the output file; if NULL, a date-stamped file -will be written to the same directory as csd_path.

- -

Value

+
+ 
mean_of_top_and_bottom_cells(
+  csd_path = NULL,
+  expression_cols,
+  top_count = 20,
+  bottom_percentile = 0.1,
+  adjacent_max = 3,
+  tissue_categories = NULL,
+  .by = "Slide ID",
+  out_path = NULL
+)
+
+
+

Arguments

+
csd_path
+

Path to a merged cell seg data, or NULL. If NULL, a file +chooser is opened to allow file selection.

+
expression_cols
+

Vector of column names to report.

+
top_count
+

The number of top-expressing cells to select for +averaging.

+
bottom_percentile
+

The cutoff for the bottom percentile cells.

+
adjacent_max
+

The maximum ratio between expression of adjacent fluors

+
tissue_categories
+

Tissue categories to include, or NULL for all

+
.by
+

The column to aggregate by

+
out_path
+

The path to the output file; if NULL, a date-stamped file +will be written to the same directory as csd_path.

+
+
+

Value

The path to the generated file.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/mean_of_top_and_bottom_cells_report.html b/docs/reference/mean_of_top_and_bottom_cells_report.html index ba7e515..3ef1b11 100644 --- a/docs/reference/mean_of_top_and_bottom_cells_report.html +++ b/docs/reference/mean_of_top_and_bottom_cells_report.html @@ -1,67 +1,12 @@ - - - - - - - -Create reports showing mean expression of top and bottom cells — mean_of_top_and_bottom_cells_report • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create reports showing mean expression of top and bottom cells — mean_of_top_and_bottom_cells_report • phenoptrReports + + - - - - -
-
- -
- -
+

Create reports showing mean expression of top and bottom cells

- Source: R/mean_of_top_and_bottom_cells.R + Source: R/mean_of_top_and_bottom_cells.R
@@ -152,69 +88,56 @@

Create reports showing mean expression of top and bottom cells

Create reports showing mean expression of top and bottom cells

- 
mean_of_top_and_bottom_cells_report(
-  merge_file,
-  config_file,
-  by,
-  tissue_categories,
-  adjacent_max
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
merge_file

Path to a merged or consolidated cell seg data file

config_file

Path to a configuration file containing -column names in the merge file, one name per line.

by

Column to aggregate by, e.g. "Slide ID" or "Annotation ID".

tissue_categories

Tissue categories to report, or NULL to use all.

adjacent_max

The maximum ratio between expression of adjacent fluors.

- -

Value

+
+ 
mean_of_top_and_bottom_cells_report(
+  merge_file,
+  config_file,
+  by,
+  tissue_categories,
+  adjacent_max
+)
+
+
+

Arguments

+
merge_file
+

Path to a merged or consolidated cell seg data file

+
config_file
+

Path to a configuration file containing +column names in the merge file, one name per line.

+
by
+

Column to aggregate by, e.g. "Slide ID" or "Annotation ID".

+
tissue_categories
+

Tissue categories to report, or NULL to use all.

+
adjacent_max
+

The maximum ratio between expression of adjacent fluors.

+
+
+

Value

None

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/merge_cell_seg_files.html b/docs/reference/merge_cell_seg_files.html index e9db258..5eabb5a 100644 --- a/docs/reference/merge_cell_seg_files.html +++ b/docs/reference/merge_cell_seg_files.html @@ -1,69 +1,14 @@ - - - - - - - -Merge inForm output from multiple fields. — merge_cell_seg_files • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Merge inForm output from multiple fields. — merge_cell_seg_files • phenoptrReports - - - - + + -
-
- -
- -
+

Merge inForm output from multiple fields.

- Source: R/merge_cell_seg_files.R + Source: R/merge_cell_seg_files.R
@@ -156,52 +92,42 @@

Merge inForm output from multiple fields.

does not include the ability to review and reject individual fields.

- 
merge_cell_seg_files(base_path, update_progress = NULL, recursive = FALSE)
- -

Arguments

- - - - - - - - - - - - - - -
base_path

Path to a directory containing files to merge. All -eligible files in this directory will be merged.

update_progress

Callback function which is called with progress.

recursive

If TRUE, will find files in subdirectories of base_path.

+
+ 
merge_cell_seg_files(base_path, update_progress = NULL, recursive = FALSE)
+
+
+

Arguments

+
base_path
+

Path to a directory containing files to merge. All +eligible files in this directory will be merged.

+
update_progress
+

Callback function which is called with progress.

+
recursive
+

If TRUE, will find files in subdirectories of base_path.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/nearest_neighbor_map.html b/docs/reference/nearest_neighbor_map.html index ec9b1ca..07bad02 100644 --- a/docs/reference/nearest_neighbor_map.html +++ b/docs/reference/nearest_neighbor_map.html @@ -1,68 +1,13 @@ - - - - - - - -Make a nearest neighbor map for a single field — nearest_neighbor_map • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Make a nearest neighbor map for a single field — nearest_neighbor_map • phenoptrReports + + - - - - -
-
- -
- -
+

Make a nearest neighbor map for a single field

- Source: R/spatial_maps.R + Source: R/spatial_maps.R
@@ -154,97 +90,77 @@

Make a nearest neighbor map for a single field

shown with any available phenotype.

- 
nearest_neighbor_map(
-  csd,
-  field_name,
-  view_number,
-  export_path,
-  phenos,
-  color1,
-  color2,
-  show_as = c("from_to", "to_from", "mutual", "none"),
-  dot_size = 3,
-  add_logo = TRUE
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
csd

Cell seg data with distance columns

field_name

Sample Name or Annotation ID to map

view_number

Image index within the composite data

export_path

Path to a directory containing composite and component -image files from inForm

phenos

Named list of phenotype definitions. Must have length 2.

color1, color2

Colors to draw the phenotype dots

show_as

Which nearest neighbors should be shown?

dot_size

Size of the dots used to show phenotypes

add_logo

Show the Akoya logo in the image?

- -

Value

- -

Returns a list containing two items:

-
plot

The plot, a ggplot object.

-
data

A tibble containing the data +

+ 
nearest_neighbor_map(
+  csd,
+  field_name,
+  view_number,
+  export_path,
+  phenos,
+  color1,
+  color2,
+  show_as = c("from_to", "to_from", "mutual", "none"),
+  dot_size = 3,
+  add_logo = TRUE
+)
+
+ +
+

Arguments

+
csd
+

Cell seg data with distance columns

+
field_name
+

Sample Name or Annotation ID to map

+
view_number
+

Image index within the composite data

+
export_path
+

Path to a directory containing composite and component +image files from inForm

+
phenos
+

Named list of phenotype definitions. Must have length 2.

+
color1, color2
+

Colors to draw the phenotype dots

+
show_as
+

Which nearest neighbors should be shown?

+
dot_size
+

Size of the dots used to show phenotypes

+
add_logo
+

Show the Akoya logo in the image?

+
+
+

Value

+

Returns a list containing two items:

plot
+

The plot, a ggplot object.

+ +
data
+

A tibble containing the data used to create the line segments in the plot, or NULL if show_as is "none".

-
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/nearest_neighbor_summary.html b/docs/reference/nearest_neighbor_summary.html index e16a02f..9cc910b 100644 --- a/docs/reference/nearest_neighbor_summary.html +++ b/docs/reference/nearest_neighbor_summary.html @@ -1,74 +1,19 @@ - - - - - - - -Summarize nearest neighbor distances — nearest_neighbor_summary • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Summarize nearest neighbor distances — nearest_neighbor_summary • phenoptrReports - + + - - - -
-
- -
- -
+

Summarize nearest neighbor distances

- Source: R/distance_helpers.R + Source: R/distance_helpers.R
@@ -166,80 +102,65 @@

Summarize nearest neighbor distances

categories.

- 
nearest_neighbor_summary(
-  csd,
-  phenotypes = NULL,
-  categories = NA,
-  details_path = NULL,
-  .by = "Slide ID",
-  extra_cols = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - -
csd

Cell seg data with Cell X Position, -Cell Y Position, field name and Phenotype columns.

phenotypes

Optional list of phenotypes to include. If omitted, -will use unique_phenotypes(csd).

categories

Optional list of tissue categories to compute within. If -omitted or NA, all cells will be included.

details_path

If present, path to save a tab-separated table -for each tissue category containing -nearest-neighbor data for each cell in the tissue category.

.by

Column to aggregate by

extra_cols

The names of extra columns to include in the detailed -results.

- -

Value

+
+ 
nearest_neighbor_summary(
+  csd,
+  phenotypes = NULL,
+  categories = NA,
+  details_path = NULL,
+  .by = "Slide ID",
+  extra_cols = NULL
+)
+
+
+

Arguments

+
csd
+

Cell seg data with Cell X Position, +Cell Y Position, field name and Phenotype columns.

+
phenotypes
+

Optional list of phenotypes to include. If omitted, +will use unique_phenotypes(csd).

+
categories
+

Optional list of tissue categories to compute within. If +omitted or NA, all cells will be included.

+
details_path
+

If present, path to save a tab-separated table +for each tissue category containing +nearest-neighbor data for each cell in the tissue category.

+
.by
+

Column to aggregate by

+
extra_cols
+

The names of extra columns to include in the detailed +results.

+
+
+

Value

A data frame with summary statistics for each phenotype pair in each Slide ID for each tissue category.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/order_by_slide_and_tissue_category.html b/docs/reference/order_by_slide_and_tissue_category.html index 4709a6f..4351b21 100644 --- a/docs/reference/order_by_slide_and_tissue_category.html +++ b/docs/reference/order_by_slide_and_tissue_category.html @@ -1,73 +1,18 @@ - - - - - - - -Order a data frame by slide ID and tissue category, putting the +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Order a data frame by slide ID and tissue category, putting the categories in the given order and the -"Total" category in the proper place. — order_by_slide_and_tissue_category • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + - - - - -
-
- -
- -
+

Order a data frame by slide ID and tissue category, putting the categories in the given order and the "Total" category in the proper place.

- Source: R/utilities.R + Source: R/utilities.R
@@ -162,54 +98,45 @@

Order a data frame by slide ID and tissue category, putting the "Total" category in the proper place.

- 
order_by_slide_and_tissue_category(d, tissue_categories, .by = "Slide ID")
- -

Arguments

- - - - - - - - - - - - - - -
d

A data frame with .by and Tissue Category columns

tissue_categories

A vector of category names in the desired order

.by

First column to sort by

- -

Value

+
+ 
order_by_slide_and_tissue_category(d, tissue_categories, .by = "Slide ID")
+
+
+

Arguments

+
d
+

A data frame with .by and Tissue Category columns

+
tissue_categories
+

A vector of category names in the desired order

+
.by
+

First column to sort by

+
+
+

Value

The input, sorted

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/spatial_map_viewer.html b/docs/reference/spatial_map_viewer.html index 6d3486c..4ae72f7 100644 --- a/docs/reference/spatial_map_viewer.html +++ b/docs/reference/spatial_map_viewer.html @@ -1,70 +1,15 @@ - - - - - - - -Run the spatial map viewer with the given data -file and export directory. — spatial_map_viewer • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Run the spatial map viewer with the given data +file and export directory. — spatial_map_viewer • phenoptrReports - + + - - - -
-
- -
- -
+

Run the spatial map viewer with the given data file and export directory.

- Source: R/spatial_map_viewer_addin.R + Source: R/spatial_map_viewer_addin.R
-

See addin_35_spatial_map_viewer() +

See addin_35_spatial_map_viewer() for a GUI front-end to this function.

- 
spatial_map_viewer(csd_path, export_path)
+
+ 
spatial_map_viewer(csd_path, export_path)
+
-

Arguments

- - - - - - - - - - -
csd_path

Path to a Consolidated_data.txt file from the consolidation +

+

Arguments

+
csd_path
+

Path to a Consolidated_data.txt file from the consolidation app or nearest_neighbors.txt or count_within.txt -file created by the analysis app.

export_path

Path to a directory containing composite and -component images for the fields in the data file.

- -

Value

- +file created by the analysis app.

+
export_path
+

Path to a directory containing composite and +component images for the fields in the data file.

+
+
+

Value

None; starts the viewer app

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/split_phenotype_column.html b/docs/reference/split_phenotype_column.html index 0d1a2b8..47677ed 100644 --- a/docs/reference/split_phenotype_column.html +++ b/docs/reference/split_phenotype_column.html @@ -1,68 +1,13 @@ - - - - - - - -Split a single phenotype column — split_phenotype_column • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Split a single phenotype column — split_phenotype_column • phenoptrReports - - - - + + -
-
- -
- -
+

Split a single phenotype column

- Source: R/split_phenotypes.R + Source: R/split_phenotypes.R
@@ -154,55 +90,49 @@

Split a single phenotype column

into multiple columns, one for each single phenotype.

- 
split_phenotype_column(csd, column)
- -

Arguments

- - - - - - - - - - -
csd

Cell seg data to use.

column

The name of the column to split

- -

Value

+
+ 
split_phenotype_column(csd, column)
+
+
+

Arguments

+
csd
+

Cell seg data to use.

+
column
+

The name of the column to split

+
+
+

Value

A new data frame with the column column replaced with individual columns per phenotype and the Confidence column(s) removed.

-

Details

- +
+
+

Details

Multiple phenotypes in the original column must be separated with "/". The names of positive phenotypes must end in "+".

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/split_phenotypes.html b/docs/reference/split_phenotypes.html index cc3c3fc..9fd9327 100644 --- a/docs/reference/split_phenotypes.html +++ b/docs/reference/split_phenotypes.html @@ -1,68 +1,13 @@ - - - - - - - -Split all phenotype columns — split_phenotypes • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Split all phenotype columns — split_phenotypes • phenoptrReports - - - - + + -
-
- -
- -
+

Split all phenotype columns

- Source: R/split_phenotypes.R + Source: R/split_phenotypes.R
@@ -154,52 +90,48 @@

Split all phenotype columns

into multiple columns, one for each single phenotype.

- 
split_phenotypes(csd)
- -

Arguments

- - - - - - -
csd

Cell seg data to use.

- -

Value

+
+ 
split_phenotypes(csd)
+
+
+

Arguments

+
csd
+

Cell seg data to use.

+
+
+

Value

A new data frame with Phenotype and Phenotype-<scheme> columns replaced with individual columns per phenotype and the Confidence column(s) removed.

-

Details

- +
+
+

Details

Multiple phenotypes in the original column must be separated with "/". The names of positive phenotypes must end in "+".

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/staining_consistency_report.html b/docs/reference/staining_consistency_report.html index 30ab68f..1034454 100644 --- a/docs/reference/staining_consistency_report.html +++ b/docs/reference/staining_consistency_report.html @@ -1,67 +1,12 @@ - - - - - - - -Actually generate the staining consistency report — staining_consistency_report • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Actually generate the staining consistency report — staining_consistency_report • phenoptrReports + + - - - - -
-
- -
- -
+

Actually generate the staining consistency report

- Source: R/staining_consistency_report_addin.R + Source: R/staining_consistency_report_addin.R
@@ -152,59 +88,48 @@

Actually generate the staining consistency report

Actually generate the staining consistency report

- 
staining_consistency_report(csd_path, marker, compartment, output_dir = NULL)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
csd_path

Path to a merge cell seg data file

marker

Name of the marker to report

compartment

Name of the compartment to report

output_dir

(Optional) Directory for the result, default -is the directory containing csd_path.

- -

Value

+
+ 
staining_consistency_report(csd_path, marker, compartment, output_dir = NULL)
+
+
+

Arguments

+
csd_path
+

Path to a merge cell seg data file

+
marker
+

Name of the marker to report

+
compartment
+

Name of the compartment to report

+
output_dir
+

(Optional) Directory for the result, default +is the directory containing csd_path.

+
+
+

Value

The path to the created file.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/unmixing_quality_report.html b/docs/reference/unmixing_quality_report.html index a19e6b6..994eb2f 100644 --- a/docs/reference/unmixing_quality_report.html +++ b/docs/reference/unmixing_quality_report.html @@ -1,70 +1,15 @@ - - - - - - - -Create an unmixing quality report for simplex samples — unmixing_quality_report • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create an unmixing quality report for simplex samples — unmixing_quality_report • phenoptrReports - - - - - - - - - - + + - - - -
-
- -
- -
+

Create an unmixing quality report for simplex samples

- Source: R/reports.R + Source: R/reports.R
@@ -158,49 +94,44 @@

Create an unmixing quality report for simplex samples

the source directory.

- 
unmixing_quality_report(export_path = NULL)
- -

Arguments

- - - - - - -
export_path

Path to a directory containing component_data files.

- -

Details

+
+ 
unmixing_quality_report(export_path = NULL)
+
+
+

Arguments

+
export_path
+

Path to a directory containing component_data files.

+
+
+

Details

The report generator tries to identify the Opal fluor for each source file by looking at the file name. It recognizes "DAPI", "AF", "Opalnnn" and "Opal_nnn". It also recognizes three leading digits as the number of an Opal fluor.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/upset_plot.html b/docs/reference/upset_plot.html index 760416c..ffac0f8 100644 --- a/docs/reference/upset_plot.html +++ b/docs/reference/upset_plot.html @@ -1,67 +1,12 @@ - - - - - - - -Create an UpSet plot showing the phenotype combinations present in data. — upset_plot • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create an UpSet plot showing the phenotype combinations present in data. — upset_plot • phenoptrReports - + + - - - -
-
- -
- -
+

Create an UpSet plot showing the phenotype combinations present in data.

- Source: R/upset_plot.R + Source: R/upset_plot.R
@@ -152,51 +88,44 @@

Create an UpSet plot showing the phenotype combinations present in data.

See http://caleydo.org/tools/upset/ for an explanation of the plot.

- 
upset_plot(csd, expected = NULL)
- -

Arguments

- - - - - - - - - - -
csd

A cell seg table with multiple Phenotype columns

expected

Optional vector of expected phenotypes. If provided, -these will be highlighted in the plot.

- -

Value

+
+ 
upset_plot(csd, expected = NULL)
+
-

An upset plot created with UpSetR::upset.

+
+

Arguments

+
csd
+

A cell seg table with multiple Phenotype columns

+
expected
+

Optional vector of expected phenotypes. If provided, +these will be highlighted in the plot.

+
+
+

Value

+

An upset plot created with UpSetR::upset.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+

- - + + diff --git a/docs/reference/write_count_within_sheet.html b/docs/reference/write_count_within_sheet.html index 8bf8115..53abced 100644 --- a/docs/reference/write_count_within_sheet.html +++ b/docs/reference/write_count_within_sheet.html @@ -1,68 +1,13 @@ - - - - - - - -Write a "count within" summary to an Excel workbook — write_count_within_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a "count within" summary to an Excel workbook — write_count_within_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write a "count within" summary to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -154,71 +90,60 @@

Write a "count within" summary to an Excel workbook

sheet in an Excel workbook.

- 
write_count_within_sheet(
-  wb,
-  stats,
-  sheet_name = "Count Within",
-  sheet_title = "Count of cells within the specified radius"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

stats

A summary data frame.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the table.

- -

See also

- -

Other output functions: -write_counts_sheet(), -write_density_sheet(), -write_expression_sheet(), -write_h_score_sheet(), -write_nearest_neighbor_summary_sheet(), -write_percents_sheet(), -write_plot_sheet(), -write_summary_sheet()

+
+ 
write_count_within_sheet(
+  wb,
+  stats,
+  sheet_name = "Count Within",
+  sheet_title = "Count of cells within the specified radius"
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
stats
+

A summary data frame.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the table.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_counts_sheet.html b/docs/reference/write_counts_sheet.html index 44f4cac..88fe6c1 100644 --- a/docs/reference/write_counts_sheet.html +++ b/docs/reference/write_counts_sheet.html @@ -1,67 +1,12 @@ - - - - - - - -Write a cell counts table to an Excel workbook — write_counts_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a cell counts table to an Excel workbook — write_counts_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write a cell counts table to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -152,72 +88,61 @@

Write a cell counts table to an Excel workbook

Write a formatted cell counts table to a sheet in an Excel workbook.

- 
write_counts_sheet(
-  wb,
-  counts,
-  sheet_name = "Cell Counts",
-  sheet_title = "Cell Counts per Phenotype"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

counts

A data frame with columns for Slide ID, Tissue Category, -and counts, such as the output of count_phenotypes.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the table.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_density_sheet(), -write_expression_sheet(), -write_h_score_sheet(), -write_nearest_neighbor_summary_sheet(), -write_percents_sheet(), -write_plot_sheet(), -write_summary_sheet()

+
+ 
write_counts_sheet(
+  wb,
+  counts,
+  sheet_name = "Cell Counts",
+  sheet_title = "Cell Counts per Phenotype"
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
counts
+

A data frame with columns for Slide ID, Tissue Category, +and counts, such as the output of count_phenotypes.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the table.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_density_sheet.html b/docs/reference/write_density_sheet.html index 9858b3b..8932237 100644 --- a/docs/reference/write_density_sheet.html +++ b/docs/reference/write_density_sheet.html @@ -1,67 +1,12 @@ - - - - - - - -Write a density table to an Excel workbook — write_density_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a density table to an Excel workbook — write_density_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write a density table to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -152,73 +88,62 @@

Write a density table to an Excel workbook

Write a formatted density table to a sheet in an Excel workbook.

- 
write_density_sheet(
-  wb,
-  densities,
-  sheet_name = "Cell Densities",
-  sheet_title = "Cell Densities (cells/mm2)"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

densities

A data frame with columns for Slide ID, Tissue Category, +

+ 
write_density_sheet(
+  wb,
+  densities,
+  sheet_name = "Cell Densities",
+  sheet_title = "Cell Densities (cells/mm2)"
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
densities
+

A data frame with columns for Slide ID, Tissue Category, Tissue Area and densities, such as the output of -compute_density_from_table.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the table.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_counts_sheet(), -write_expression_sheet(), -write_h_score_sheet(), -write_nearest_neighbor_summary_sheet(), -write_percents_sheet(), -write_plot_sheet(), -write_summary_sheet()

+compute_density_from_table.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the table.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_expression_sheet.html b/docs/reference/write_expression_sheet.html index b61acb2..163a97f 100644 --- a/docs/reference/write_expression_sheet.html +++ b/docs/reference/write_expression_sheet.html @@ -1,67 +1,12 @@ - - - - - - - -Write an expression table to an Excel workbook — write_expression_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write an expression table to an Excel workbook — write_expression_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write an expression table to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -152,73 +88,62 @@

Write an expression table to an Excel workbook

Write a formatted cell expression table to a sheet in an Excel workbook.

- 
write_expression_sheet(
-  wb,
-  exprs,
-  sheet_name = "Mean Expression",
-  sheet_title = "Mean Expression"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

exprs

A data frame with columns for Slide ID, Tissue Category, +

+ 
write_expression_sheet(
+  wb,
+  exprs,
+  sheet_name = "Mean Expression",
+  sheet_title = "Mean Expression"
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
exprs
+

A data frame with columns for Slide ID, Tissue Category, and mean expression, such as the output of -compute_mean_expression_many. Count columns are not reported.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the table.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_counts_sheet(), -write_density_sheet(), -write_h_score_sheet(), -write_nearest_neighbor_summary_sheet(), -write_percents_sheet(), -write_plot_sheet(), -write_summary_sheet()

+compute_mean_expression_many. Count columns are not reported.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the table.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_h_score_sheet.html b/docs/reference/write_h_score_sheet.html index d296f01..3b00554 100644 --- a/docs/reference/write_h_score_sheet.html +++ b/docs/reference/write_h_score_sheet.html @@ -1,67 +1,12 @@ - - - - - - - -Write an H-Score table to an Excel workbook — write_h_score_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write an H-Score table to an Excel workbook — write_h_score_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write an H-Score table to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -152,79 +88,66 @@

Write an H-Score table to an Excel workbook

Write a formatted H-Score table to a sheet in an Excel workbook.

- 
write_h_score_sheet(
-  wb,
-  h_score,
-  sheet_name = NULL,
-  sheet_title = NULL,
-  marker = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

h_score

A data frame with columns for Slide ID, Tissue Category, -and percent, such as the output of compute_h_score.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the table. If omitted, -the title will be inferred from the h_score data if possible.

marker

Optional marker name to add to the default sheet title. -Ignored if sheet_title is provided.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_counts_sheet(), -write_density_sheet(), -write_expression_sheet(), -write_nearest_neighbor_summary_sheet(), -write_percents_sheet(), -write_plot_sheet(), -write_summary_sheet()

+
+ 
write_h_score_sheet(
+  wb,
+  h_score,
+  sheet_name = NULL,
+  sheet_title = NULL,
+  marker = NULL
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
h_score
+

A data frame with columns for Slide ID, Tissue Category, +and percent, such as the output of compute_h_score.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the table. If omitted, +the title will be inferred from the h_score data if possible.

+
marker
+

Optional marker name to add to the default sheet title. +Ignored if sheet_title is provided.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_mean_of_top_and_bottom_charts.html b/docs/reference/write_mean_of_top_and_bottom_charts.html index c2b6fd3..2fd6850 100644 --- a/docs/reference/write_mean_of_top_and_bottom_charts.html +++ b/docs/reference/write_mean_of_top_and_bottom_charts.html @@ -1,71 +1,16 @@ - - - - - - - -Create summary charts from the results of mean_of_top_and_bottom_cells — write_mean_of_top_and_bottom_charts • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create summary charts from the results of mean_of_top_and_bottom_cells — write_mean_of_top_and_bottom_charts • phenoptrReports - - - - - - - - - - - - - + + -
-
- -
- -
+

Create summary charts from the results of mean_of_top_and_bottom_cells

- Source: R/mean_of_top_and_bottom_cells.R + Source: R/mean_of_top_and_bottom_cells.R

Create a Microsoft Word file or HTML document containing summary charts -derived from the output of mean_of_top_and_bottom_cells +derived from the output of mean_of_top_and_bottom_cells with default parameters. The file type is determined by the file extension of output_path, which must be either .docx or .html.

- 
write_mean_of_top_and_bottom_charts(
-  worksheet_path,
-  output_path,
-  .by = "Slide ID"
-)
- -

Arguments

- - - - - - - - - - - - - - -
worksheet_path

Path to an Excel file containing sheets written -by mean_of_top_and_bottom_cells.

output_path

Path to write the resulting file.

.by

The aggregation column name

+
+ 
write_mean_of_top_and_bottom_charts(
+  worksheet_path,
+  output_path,
+  .by = "Slide ID"
+)
+
+
+

Arguments

+
worksheet_path
+

Path to an Excel file containing sheets written +by mean_of_top_and_bottom_cells.

+
output_path
+

Path to write the resulting file.

+
.by
+

The aggregation column name

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_nearest_neighbor_summary_sheet.html b/docs/reference/write_nearest_neighbor_summary_sheet.html index 17a7496..b845256 100644 --- a/docs/reference/write_nearest_neighbor_summary_sheet.html +++ b/docs/reference/write_nearest_neighbor_summary_sheet.html @@ -1,68 +1,13 @@ - - - - - - - -Write a nearest neighbor summary to an Excel workbook — write_nearest_neighbor_summary_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a nearest neighbor summary to an Excel workbook — write_nearest_neighbor_summary_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write a nearest neighbor summary to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -154,71 +90,60 @@

Write a nearest neighbor summary to an Excel workbook

sheet in an Excel workbook.

- 
write_nearest_neighbor_summary_sheet(
-  wb,
-  stats,
-  sheet_name = "Nearest Neighbors",
-  sheet_title = "Nearest Neighbor Distances for Phenotype Pairs (microns)"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

stats

A summary data frame.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the table.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_counts_sheet(), -write_density_sheet(), -write_expression_sheet(), -write_h_score_sheet(), -write_percents_sheet(), -write_plot_sheet(), -write_summary_sheet()

+
+ 
write_nearest_neighbor_summary_sheet(
+  wb,
+  stats,
+  sheet_name = "Nearest Neighbors",
+  sheet_title = "Nearest Neighbor Distances for Phenotype Pairs (microns)"
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
stats
+

A summary data frame.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the table.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_percents_sheet.html b/docs/reference/write_percents_sheet.html index dc2d9f7..e1f6415 100644 --- a/docs/reference/write_percents_sheet.html +++ b/docs/reference/write_percents_sheet.html @@ -1,67 +1,12 @@ - - - - - - - -Write a cell percent table to an Excel workbook — write_percents_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a cell percent table to an Excel workbook — write_percents_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write a cell percent table to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -152,72 +88,61 @@

Write a cell percent table to an Excel workbook

Write a formatted cell percent table to a sheet in an Excel workbook.

- 
write_percents_sheet(
-  wb,
-  percents,
-  sheet_name = "Cell Percents",
-  sheet_title = "Percentage of Total Cells"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

percents

A data frame with columns for Slide ID, Tissue Category, -and percent.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the table.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_counts_sheet(), -write_density_sheet(), -write_expression_sheet(), -write_h_score_sheet(), -write_nearest_neighbor_summary_sheet(), -write_plot_sheet(), -write_summary_sheet()

+
+ 
write_percents_sheet(
+  wb,
+  percents,
+  sheet_name = "Cell Percents",
+  sheet_title = "Percentage of Total Cells"
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
percents
+

A data frame with columns for Slide ID, Tissue Category, +and percent.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the table.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_plot_sheet.html b/docs/reference/write_plot_sheet.html index d5ff7ca..8eda396 100644 --- a/docs/reference/write_plot_sheet.html +++ b/docs/reference/write_plot_sheet.html @@ -1,67 +1,12 @@ - - - - - - - -Write a plot to an Excel workbook — write_plot_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a plot to an Excel workbook — write_plot_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write a plot to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -152,71 +88,60 @@

Write a plot to an Excel workbook

Write a plot to a sheet in an Excel workbook.

- 
write_plot_sheet(
-  wb,
-  plot,
-  sheet_name = "Phenotypes",
-  sheet_title = "All combinations of phenotypes in all slides"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

plot

A plot such as the output from upset_plot.

sheet_name

Optional name for the worksheet.

sheet_title

Optional title header for the plot.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_counts_sheet(), -write_density_sheet(), -write_expression_sheet(), -write_h_score_sheet(), -write_nearest_neighbor_summary_sheet(), -write_percents_sheet(), -write_summary_sheet()

+
+ 
write_plot_sheet(
+  wb,
+  plot,
+  sheet_name = "Phenotypes",
+  sheet_title = "All combinations of phenotypes in all slides"
+)
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
plot
+

A plot such as the output from upset_plot.

+
sheet_name
+

Optional name for the worksheet.

+
sheet_title
+

Optional title header for the plot.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_session_info.html b/docs/reference/write_session_info.html index 28c9170..6e690aa 100644 --- a/docs/reference/write_session_info.html +++ b/docs/reference/write_session_info.html @@ -1,68 +1,13 @@ - - - - - - - -Write session info to a file — write_session_info • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write session info to a file — write_session_info • phenoptrReports - + + - - - -
-
- -
- -
+

Write session info to a file

- Source: R/reports.R + Source: R/reports.R
-

This will write the output of sessioninfo::session_info() -if it is available, otherwise utils::sessionInfo() is used.

+

This will write the output of sessioninfo::session_info() +if it is available, otherwise utils::sessionInfo() is used.

- 
write_session_info(path)
- -

Arguments

- - - - - - -
path

Path to the output file

- -

Value

+
+ 
write_session_info(path)
+
+
+

Arguments

+
path
+

Path to the output file

+
+
+

Value

None

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_sheet.html b/docs/reference/write_sheet.html index 11c9ff6..0391e3a 100644 --- a/docs/reference/write_sheet.html +++ b/docs/reference/write_sheet.html @@ -1,46 +1,5 @@ - - - - - - - -Write a single sheet with formatting common to all sheets. — write_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a single sheet with formatting common to all sheets. — write_sheet • phenoptrReports - - - - - - - - - - - - - + + -
-
- -
- -
+

Write a single sheet with formatting common to all sheets.

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
-
    -

  • Bold, centered header

    • +

    • Bold, centered header

    • Bold column headers

    • Bold Slide ID column

    • Two-row page title

    • Page breaks as needed

      • -
    - +
+ +
+ 
write_sheet(
+  wb,
+  d,
+  sheet_name,
+  sheet_title,
+  header_col,
+  keepNA = TRUE,
+  addGrid = TRUE
+)
- 
write_sheet(
-  wb,
-  d,
-  sheet_name,
-  sheet_title,
-  header_col,
-  keepNA = TRUE,
-  addGrid = TRUE
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

d

A data frame to write.

sheet_name

Name for the worksheet.

sheet_title

Title header for the plot.

header_col

Column number to start the sheet_title

keepNA

If TRUE, NA values are written as #N/A; else they are blank.

addGrid

If TRUE, grid lines (and page breaks) are added based +

+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
d
+

A data frame to write.

+
sheet_name
+

Name for the worksheet.

+
sheet_title
+

Title header for the plot.

+
header_col
+

Column number to start the sheet_title

+
keepNA
+

If TRUE, NA values are written as #N/A; else they are blank.

+
addGrid
+

If TRUE, grid lines (and page breaks) are added based on the tissue categories in the data. If FALSE, no grid lines are added -and page breaks are added where needed.

- -

Value

- +and page breaks are added where needed.

+
+
+

Value

Invisibly, the number of columns added with TMA info (0, 3, or 4)

-

Details

- +
+
+

Details

If the provided data has TMA core information embedded in a Sample Name column, add columns with the TMA info.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_summary_charts.html b/docs/reference/write_summary_charts.html index 3d13d50..5b16140 100644 --- a/docs/reference/write_summary_charts.html +++ b/docs/reference/write_summary_charts.html @@ -1,68 +1,13 @@ - - - - - - - -Create summary charts from the results of an analysis — write_summary_charts • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create summary charts from the results of an analysis — write_summary_charts • phenoptrReports - - - - + + -
-
- -
- -
+

Create summary charts from the results of an analysis

- Source: R/reports.R + Source: R/reports.R
@@ -154,68 +90,54 @@

Create summary charts from the results of an analysis

derived from an analysis.

- 
write_summary_charts(
-  workbook_path,
-  output_path,
-  .by = "Slide ID",
-  max_slides_per_plot = 20,
-  max_heatmaps_per_plot = 8
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
workbook_path

Path to an Excel file containing sheets written -by write_counts_sheet, etc.

output_path

Path to write the resulting file.

.by

Name of the grouping parameter in the worksheets.

max_slides_per_plot

Maximum number of slides or samples -to show on each plot.

max_heatmaps_per_plot

Maximum number of heatmaps to show -on each plot.

+
+ 
write_summary_charts(
+  workbook_path,
+  output_path,
+  .by = "Slide ID",
+  max_slides_per_plot = 20,
+  max_heatmaps_per_plot = 8
+)
+
+
+

Arguments

+
workbook_path
+

Path to an Excel file containing sheets written +by write_counts_sheet, etc.

+
output_path
+

Path to write the resulting file.

+
.by
+

Name of the grouping parameter in the worksheets.

+
max_slides_per_plot
+

Maximum number of slides or samples +to show on each plot.

+
max_heatmaps_per_plot
+

Maximum number of heatmaps to show +on each plot.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+

- - + + diff --git a/docs/reference/write_summary_report.html b/docs/reference/write_summary_report.html index c30849a..627cd82 100644 --- a/docs/reference/write_summary_report.html +++ b/docs/reference/write_summary_report.html @@ -1,68 +1,13 @@ - - - - - - - -Create a summary report for a cell seg data file — write_summary_report • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create a summary report for a cell seg data file — write_summary_report • phenoptrReports - - - - + + -
-
- -
- -
+

Create a summary report for a cell seg data file

- Source: R/reports.R + Source: R/reports.R
@@ -154,60 +90,48 @@

Create a summary report for a cell seg data file

in a single cell seg data file.

- 
write_summary_report(
-  csd_path = NULL,
-  csd = NULL,
-  dataset_name = NULL,
-  output_path
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
csd_path

Path to cell seg data file, or NULL.

csd

Cell seg table, or NULL.

dataset_name

Descriptive name of the dataset.

output_path

Path to write the resulting HTML file.

+
+ 
write_summary_report(
+  csd_path = NULL,
+  csd = NULL,
+  dataset_name = NULL,
+  output_path
+)
+
+
+

Arguments

+
csd_path
+

Path to cell seg data file, or NULL.

+
csd
+

Cell seg table, or NULL.

+
dataset_name
+

Descriptive name of the dataset.

+
output_path
+

Path to write the resulting HTML file.

+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/reference/write_summary_sheet.html b/docs/reference/write_summary_sheet.html index 7d33bee..5b03218 100644 --- a/docs/reference/write_summary_sheet.html +++ b/docs/reference/write_summary_sheet.html @@ -1,68 +1,13 @@ - - - - - - - -Write a summary table to an Excel workbook — write_summary_sheet • phenoptrReports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Write a summary table to an Excel workbook — write_summary_sheet • phenoptrReports - + + - - - -
-
- -
- -
+

Write a summary table to an Excel workbook

- Source: R/excel_helpers.R + Source: R/excel_helpers.R
@@ -154,62 +90,53 @@

Write a summary table to an Excel workbook

a sheet in an Excel workbook.

- 
write_summary_sheet(wb, summary_table, sheet_name = "Slide Summary")
- -

Arguments

- - - - - - - - - - - - - - -
wb

An openxlsx Workbook from openxlsx::createWorkbook

summary_table

A data frame with columns for Slide ID and count.

sheet_name

Optional name for the worksheet.

- -

See also

- -

Other output functions: -write_count_within_sheet(), -write_counts_sheet(), -write_density_sheet(), -write_expression_sheet(), -write_h_score_sheet(), -write_nearest_neighbor_summary_sheet(), -write_percents_sheet(), -write_plot_sheet()

+
+ 
write_summary_sheet(wb, summary_table, sheet_name = "Slide Summary")
+
+ +
+

Arguments

+
wb
+

An openxlsx Workbook from openxlsx::createWorkbook

+
summary_table
+

A data frame with columns for Slide ID and count.

+
sheet_name
+

Optional name for the worksheet.

+
+
+
-
-
-

Developed by Kent S Johnson, Akoya Biosciences.

+
+

Developed by Kent S Johnson, Akoya Biosciences.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.1.

-
-
+
- - + + diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 9304ec8..d07f654 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -1,8 +1,47 @@ + + http://akoyabio.github.io/phenoptrReports/404.html + + + http://akoyabio.github.io/phenoptrReports/articles/analysis.html + + + http://akoyabio.github.io/phenoptrReports/articles/component_levels_report.html + + + http://akoyabio.github.io/phenoptrReports/articles/consolidation.html + + + http://akoyabio.github.io/phenoptrReports/articles/index.html + + + http://akoyabio.github.io/phenoptrReports/articles/spatial_map_viewer.html + + + http://akoyabio.github.io/phenoptrReports/articles/staining_consistency_report.html + + + http://akoyabio.github.io/phenoptrReports/articles/top_20_bottom_10_report.html + + + http://akoyabio.github.io/phenoptrReports/articles/unmixing_error.html + + + http://akoyabio.github.io/phenoptrReports/articles/unmixing_quality_report.html + + + http://akoyabio.github.io/phenoptrReports/authors.html + http://akoyabio.github.io/phenoptrReports/index.html + + http://akoyabio.github.io/phenoptrReports/LICENSE-text.html + + + http://akoyabio.github.io/phenoptrReports/news/index.html + http://akoyabio.github.io/phenoptrReports/reference/addin_10_merge.html @@ -27,6 +66,9 @@ http://akoyabio.github.io/phenoptrReports/reference/addin_70_staining_consistency_report.html + + http://akoyabio.github.io/phenoptrReports/reference/analysis_app.html + http://akoyabio.github.io/phenoptrReports/reference/choose_directory.html @@ -60,6 +102,12 @@ http://akoyabio.github.io/phenoptrReports/reference/compute_positivity_many.html + + http://akoyabio.github.io/phenoptrReports/reference/consolidate_addin.html + + + http://akoyabio.github.io/phenoptrReports/reference/consolidate_and_split_cell_seg_data.html + http://akoyabio.github.io/phenoptrReports/reference/consolidate_and_summarize_cell_seg_data.html @@ -75,12 +123,27 @@ http://akoyabio.github.io/phenoptrReports/reference/discrete_colors.html + + http://akoyabio.github.io/phenoptrReports/reference/field_column.html + + + http://akoyabio.github.io/phenoptrReports/reference/index.html + http://akoyabio.github.io/phenoptrReports/reference/mean_of_top_and_bottom_cells.html http://akoyabio.github.io/phenoptrReports/reference/mean_of_top_and_bottom_cells_report.html + + http://akoyabio.github.io/phenoptrReports/reference/merge_addin.html + + + http://akoyabio.github.io/phenoptrReports/reference/merge_and_split_cell_seg_data.html + + + http://akoyabio.github.io/phenoptrReports/reference/merge_and_summarize_cell_seg_data.html + http://akoyabio.github.io/phenoptrReports/reference/merge_cell_seg_files.html @@ -105,12 +168,24 @@ http://akoyabio.github.io/phenoptrReports/reference/staining_consistency_report.html + + http://akoyabio.github.io/phenoptrReports/reference/unmixing_error_addin.html + + + http://akoyabio.github.io/phenoptrReports/reference/unmixing_error_report.html + + + http://akoyabio.github.io/phenoptrReports/reference/unmixing_quality_addin.html + http://akoyabio.github.io/phenoptrReports/reference/unmixing_quality_report.html http://akoyabio.github.io/phenoptrReports/reference/upset_plot.html + + http://akoyabio.github.io/phenoptrReports/reference/validate_phenotype_definitions.html + http://akoyabio.github.io/phenoptrReports/reference/write_counts_sheet.html @@ -153,25 +228,4 @@ http://akoyabio.github.io/phenoptrReports/reference/write_summary_sheet.html - - http://akoyabio.github.io/phenoptrReports/articles/analysis.html - - - http://akoyabio.github.io/phenoptrReports/articles/component_levels_report.html - - - http://akoyabio.github.io/phenoptrReports/articles/consolidation.html - - - http://akoyabio.github.io/phenoptrReports/articles/spatial_map_viewer.html - - - http://akoyabio.github.io/phenoptrReports/articles/staining_consistency_report.html - - - http://akoyabio.github.io/phenoptrReports/articles/top_20_bottom_10_report.html - - - http://akoyabio.github.io/phenoptrReports/articles/unmixing_quality_report.html -