gimap performs analysis of dual-targeting CRISPR screening data, with the goal of aiding the identification of genetic interactions (e.g. cooperativity, synthetic lethality) in models of disease and other biological contexts. gimap analyzes functional genomic data generated by the pgPEN (paired guide RNAs for genetic interaction mapping) approach, quantifying growth effects of single and paired gene knockouts upon application of a CRISPR library. A multitude of CRISPR screen types can be used for this analysis, with helpful descriptions found in this review (https://www.nature.com/articles/s43586-021-00093-4). Use of pgPEN and GI-mapping in a paired gRNA format can be found here (https://pubmed.ncbi.nlm.nih.gov/34469736/).
It is based off of the original code and research from the Berger Lab stored in this repository: https://github.com/FredHutch/GI_mapping
In order to run this pipeline you will need R and to install the gimap package and its dependencies. In R you can run this to install the package:
install.packages("remotes")
remotes::install_github("FredHutch/gimap")
Now you can go to our quick start tutorial to get started!
We also have tutorial examples that show how to run timepoint or treatment experimental set ups with gimap:
Follow the steps there that will walk you through the example data. Then you can tailor that tutorial to use your own data.