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We are designing a CRISPR/Cas9 experiment and thinking of the down-stream data analyses.
Are there any R packages for analysing raw NGS read count data from pooled genetic screens using CRIPSR/Cas9 to disrupt gene expression in a population of cells? I guess we will need to start with basics, i.e. sequences processing, data exploration, visualisation etc.
Assuming you mean CRISPR screens targeting many loci (for example using the GeCKO library) there is an R package here.
It uses a linear mixed effect model to compare guide counts before and after a selection step, allowing for multiple guides/gene and multiple replicates. It can also do the initial read alignment AFAIK and the author should be quite responsive in case you have questions.
Another option could be the python program MAGeCK
From my experience, there is few about CRISPR pooled screenings in R. One of them is ScreenBEAM. It uses a linear mixture model to determine significance at gene level by considering all the guides together at the same step in the analysis. However, it does not work very well for me.
There are other ways of analyze these screenings outside of R that are easy to use such the suggested MAGeCK or others such HiTSelect, BAGEL or CRISPR-Analyzer.
CRISPR-Analyzer is an online tool that could be useful and that recapitulates some of the mentioned methods in a single analysis. However, if you want to work from command line I would recommend you BAGEL for gene essentiality experiments and MAGeCK for other experimental setup (i.e, control vs treatment)
Sorry for not putting all the links but I can only put two at the moment!
