iAnalyzeR

An analytical pipeline for powered analysis of CRISPR screens

Setting up the environment

Use the following command to create a conda environment with the essential packages used by iAnalyzeR.

conda env create --file=iAnalyzeR.yaml
conda activate iAnalyzeR

Run iAnalyzeR

Create the metadata file

The metadata file resides in the working directory and lists the required information for each sample (e.g. sample name, path to files, sample type, and etc). For example:

sample	fastq	lib.type	sample.type	sample.rep
hi_r1	hi_r1.fastq.gz	F	high	1
lo_r1	ro_l1.fastq.gz	R	low	1

Run the analysis

The following command will then run the analysis:

python iAnalyzer.py --runMode --ref=<ref> <metadata> <formula> <outfile.txt>

Options

Run python iAnalyzer.py for usage. The following are the options:

1. --runMode vs. --printMode: --printMode prints all the commands that are run
2. -a or --aligner: The aligner used (currently only bowtie2 supported)
3. -w or --weighting: Method for combining z-score. Options are 'n' (sample size), 'SE' (standard error), and 'SES' (standardized effect size) (default SES)
4. --hasUMI or --noUMI: Whether reads contain UMI or not
5. --reflib: The bowtie2 index basename (e.g. CRISPRi_v2_human_library for CRISPRi_v2_human_library.fa)
6. --ref: The reference samples that others are compare to (e.g. 'low' in example above)
7. formula: The design formula (e.g. ~sample.type in example above, i.e. high vs. low)