Crispy

A lightweight versatile pipeline for crispr-screening analysis.

Features

• supports both single sgRNA and tiling methods and their derivatives.
• comprehensive QC
• more fine-tuned controls
  • various choice of normalization
  • various statistical model
  • cutoff for sgRNA count, reads, pvalues, region, etc.

Demo

• run ./demo.sh to check if the pipeline works
• run ./test.sh to test the latest feature

More Examples

• read moreExample.sh for optimal parameters for your experiments.

Read Counts

• to generate read count table as input for crispy.sh, checkout counter/counter.demo.sh
• run counter/counter.py -h

Todos

• discrepency between regions and peaks. (optimize macs2 parameters.)
• automate read counts and QC

history

• v1.5.0:

  • included scripts used to merge statistics in preparation for the manuscript.

• v1.4.2:

  • included a "fc.bedgraph" fold change track in the output. This is the track for high resolution mean fold change.
  • included a "region.hres.bedgraph" track in the output. This is the track for high resolution RRA signal.
  • minor: counter.py example updated

• v1.4.1:

  • included an "sgRNA_all.bedgraph" track in the output. This is the track to QC pvalues of all input sgRNAs.

• v1.4:

  • final peak calling using in-house script replicating CREST-seq

• v1.3.8:

  • Included FDR guideline for "-n" pvalue cutoff choice.

• v1.3.7:

  • Highlight positive sgRNA based on -n and -d

• v1.3.6:

  • Now qc plot includes negative and positive sgRNAs as reference to guide user pick pvalue cutoff for '-n $NBCUTOFF'.

• v1.3.5:

  • Qnorm supports batch operator using ";" and ",". eg. -q "cis1,cis2;ctr1,ctr2;high1,high2"
  • More QC option
    • MIN_CPM filter (-u) and MIN_CPM_RATIO filter (-v).
  • More QC plot
    • Violin + Boxplot for read count distribution
    • Read count density plot

• v1.3:

  • added support for direction (use -d 1 for enriched sgRNA [up-regulator], -d -1 for depleted sgRNA [down-regulator] )
  • added support for aggregation methods (use -m [RRA, min,geom.mean,median,stuart]. Default=RRA)
  • added support for quantile normalization within fgs and bgs. (use -q flag. Defualt=False if not specified.)
  • bug fix
  • removed cluttered output files. Each run now have sgRNA signals, region signals and final peak signals.

• v1.2:

  • Counter template included.
  • Support for experiments without replication.

Licence

• MIT