crispr-screen-analysis

name	crispr-screen-analysis
description	Analyze CRISPR pooled screens using MAGeCK. Accepts a raw count table or FASTQ files. Runs MAGeCK RRA (pairwise test) or MAGeCK MLE (multi-condition). Produces gene-level hit rankings, volcano plots, sgRNA rank plots, and hit summary figures for both positive and negative selection. Supports genome-wide KO screens, CRISPRi, and CRISPRa experiments.

CRISPR Screen Analysis (MAGeCK)

Purpose

Run a complete CRISPR pooled screen analysis pipeline using MAGeCK. Starting from either a raw count matrix or FASTQ files, identify positively and negatively selected genes, and generate publication-quality figures.

Use when

• the user has a CRISPR screen count table and wants to identify hits
• the user wants to find essential genes (negative selection) or enriched genes (positive selection)
• the user wants to compare treatment vs control conditions in a pooled screen
• the user has multiple conditions or time points (use MLE mode)
• the user has raw FASTQ files from a pooled screen and wants to go from reads to hits
• the user mentions MAGeCK, RRA, beta score, sgRNA count, or pooled screen analysis
• the user wants a volcano plot, rank plot, or gene score plot from screen data

Do not use when

• the user wants arrayed screen analysis (not pooled)
• the user wants single-cell CRISPR screen analysis (Perturb-seq / CROP-seq)
• the user wants to design sgRNAs (use design-sgrnas-by-gene instead)
• the user has only a gene hit list without raw count data

Supported modes

Mode	Input	When to use
test	count table TSV	Pairwise comparison (treatment vs control); standard RRA
mle	count table TSV + design matrix	Multiple conditions, time-course, or complex designs
count	FASTQ files + sgRNA library	Convert raw reads to count table
all	FASTQ files + library	Full pipeline: count → test

Inputs

• --count-table — TSV with columns: sgRNA, gene, sample1, sample2, ... (required for test/mle)
• --treatment — comma-separated sample column names for the treatment group
• --control — comma-separated sample column names for the control group
• --mode — test (default), mle, count, or all
• --fastq — space-separated FASTQ paths (for count/all mode)
• --library — sgRNA library file: TSV with columns sgRNA_id, sequence, gene (for count mode)
• --design-matrix — tab-separated design matrix file (for mle mode)
• --norm-method — median (default), total, control, or none
• --fdr-cutoff — FDR significance threshold (default 0.25)
• --lfc-cutoff — |log2FC| threshold for volcano plot labeling (default 1.0)
• --gene-lfc-method — median or alphamedian (default median)
• --top-n — number of top hits to label in plots (default 20)
• --prefix — output file prefix (default screen)
• --outdir — output directory (default ./crispr_screen_results/)

Outputs

File	Description
{prefix}.gene_summary.txt	MAGeCK gene-level results (RRA scores, p-values, FDR)
{prefix}.sgrna_summary.txt	sgRNA-level results (LFC, p-value per guide)
{prefix}_volcano.png	Gene-level volcano plot (neg/pos selection)
{prefix}_rank_neg.png	Negative selection rank plot (essential genes)
{prefix}_rank_pos.png	Positive selection rank plot
{prefix}_hit_summary.png	Top hit genes bar chart
{prefix}_sgrna_scatter.png	sgRNA-level LFC scatter (treatment vs control)
{prefix}_qc.png	Read count distribution and Gini index QC
{prefix}_hits.tsv	Filtered hit gene table (FDR < cutoff)
{prefix}_count_table.txt	(count mode) Normalized count table

Execution

# Pairwise test (most common)
python scripts/crispr_screen_analysis.py \
  --count-table counts.txt \
  --treatment Day14_rep1,Day14_rep2 \
  --control Day0_rep1,Day0_rep2 \
  --mode test \
  --outdir results/

# MLE with design matrix
python scripts/crispr_screen_analysis.py \
  --count-table counts.txt \
  --mode mle \
  --design-matrix design.txt \
  --outdir results/

# From FASTQ files
python scripts/crispr_screen_analysis.py \
  --fastq sample1.fastq.gz sample2.fastq.gz \
  --library sgrna_library.txt \
  --treatment sample1 \
  --control sample2 \
  --mode all \
  --outdir results/

Parameter decision guide

Signal in user request	Parameter to set
"pairwise", "treatment vs control", "two groups", "KO screen"	--mode test
"multiple conditions", "time course", "complex design", "beta score"	--mode mle
"from FASTQ", "raw reads", "sequencing data"	--mode count or --mode all
"essential genes", "negative selection", "dropout"	--mode test; focus on neg.score column
"enriched genes", "positive selection", "gain of function", "CRISPRa"	--mode test; focus on pos.score column
"more stringent", "high confidence hits only"	--fdr-cutoff 0.05
"permissive", "screening", "exploratory"	--fdr-cutoff 0.25 (default)
"median normalization" or no mention	--norm-method median (default)
"spike-in controls", "non-targeting controls for normalization"	--norm-method control
"label top N hits"	--top-n N
replicate columns named Day0_rep1, Day0_rep2	--control Day0_rep1,Day0_rep2
replicate columns named treated_A, treated_B	--treatment treated_A,treated_B
"strong effect size only"	--lfc-cutoff 1.5 or --lfc-cutoff 2.0

MAGeCK installation note

MAGeCK must be installed separately. The recommended method is conda:

conda install -c bioconda mageck

Or via pip (Python-only implementation):

pip install mageck

This skill will automatically detect whether MAGeCK is available and fall back to a Python re-implementation of the core RRA algorithm if it is not installed.