This repository contains a Biodepot-workflow-builder (Bwb) workflow to run MAGeCK count and a Jupyter Notebook for comparing the outputs of gene count table between samples from MSK (original data providers) and Bwb (reprocessed from the workflow). After obtaining counts, MAGeCK test executes gene rankings for provided screens. The final step takes MAGeCK test gene ranking outputs for each screen and get their minimum p-values and minimum FDR values, as well as create volcano plots from these minimum values.
MAGeCK Count: This step involves running the MAGeCK count tool (version 0.5.9.5) to quantify gRNA abundance from sequencing data. Main command is mageck count. Inputs are fastq files, outputs are gene count tables for each fastq file.
Combine counts: Combine counts obtained from mageck count into a single count table. Gene counts are summed based on their sample, if multiple fastq files are used for each sample. Summary statistics from mageck count, originally from each fastq file, are summarized for each sample.
MAGeCK test: Use the count table to get sgRNA and gene rankings.
Minimum p-value FDR and volcano plots: Take mageck test gene ranking outputs for each screen/prefix and extract the minimum p-values and minimum FDR values. Outputs are sorted and exported to separate text files. Includes the option to create plotly volcano plots from minimum p-values & FDR outputs for each screen/prefix.
This repository has publicly-available The included data is from the following study:
Rosen BP, Li QV, Cho HS, Liu D et al. Parallel genome-scale CRISPR-Cas9 screens uncouple human pluripotent stem cell identity versus fitness. Nat Commun 2024 Oct 17;15(1):8966. PMID: 39419994
NCBI GEO public access is located here.
The workflow uses 1_E8_T0, 2_NE_GFP_high, 3_NE_GFP_low, and 7_E8_control samples (4 of the original 8) as workflow test samples. Downsampled versions of their fastq files are included in this repository for fast test purposes.
- Bwb
- Python 3.x
- Pandas
- NumPy
- Docker
This repository uses MAGeCK, a tool created by Li, et al.
Li, W., Xu, H., Xiao, T. et al. MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome Biol 15, 554 (2014). https://doi.org/10.1186/s13059-014-0554-4
- Installation can be found on SOURCEFORGE
- Source code can be found on Bitbucket
- MorPhiC MSK team for providing the original data and processing scripts.
- Contributors to the MAGeCK tool.