denoisingCTF: a CyTOF denoising R package

Here we present a noise removal R package for CyTOF data. You can either use the main function rm_noise to remove the noise applying the current trained models, or train your own models and then call them into the main function.

Installation

You will need to install the devtools CRAN package. All other dependencies will be automatically installed with the package installation.

# Install devtools
install.packages("devtools")

# Install denoisingCTF
devtools::install_github("msenosain/denoisingCTF")

Usage

Denoising CyTOF data

This function will remove zeros, beads and debris from the FCS files in the current working directory using previously trained models.

library(denoisingCTF)
# Set working directory in folder with files to be denoised
rm_noise(file_type = '.fcs|.FCS', rm_beads = TRUE, rm_debris = TRUE,
    use.current.model.beads = TRUE, use.current.model.debris = TRUE,
    alg_db = 'RF', alg_bd = 'RF')

Preprocessing datasets and model training

If you want to train your own classification models for beads and debris, you can do it following these steps:

1. Beads Model:

# Unsupervised beads detection and training/testing data sets generation.
Beads_TrainTest(sample_size = 40, method = 'k_means', 
    bsample = 5000, class_col = 'BeadsSmp_ID')

# Train model
TrainModel(train_set, test_set, alg = 'all', class_col = 'BeadsSmp_ID', 
    seed = 40, name_0 = 'cells', name_1 = 'beads', label = 'beads',
    allowParallel = T, free_cores = 2)

2. Debris model:

# Removal of zeros, beads and addition of row ID column
pre_gate(sample_size=30, model_beads=model_beads, alg_bd = 'RF') 

# Manually gate debris and dead cells using Gaussian Parameters and a live/dead cell marker.

# Comparison of pre-gated and post-gated files, noise labeling and training/testing data sets generation.
post_gate(bsample = 5000, path_pregated = '../') 

# Train model
TrainModel(train_set, test_set, alg = 'all', class_col = 'GP_Noise', 
    seed = 40, name_0 = 'cells', name_1 = 'debris', label = 'debris', 
    allowParallel = T, free_cores = 2)

Tutorial

For a detailed example, see our tutorial.

Debris and beads models evaluation

For further details on these models, click here.