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ACER

The goal of ACER is to test for differential essentiality between sets of samples from a CRISPR knockout screen [1]. See vignettes(package=ACER) for detailed discussion.

Installation

You can install the released version of ACER from GitHub with:

install_github("ACER")

Basic Analysis

To determine differential essentiality, run the following commands (shown with example data):

library(ACER)
newDataObj <- DataObj$new(masterFiles = system.file('extdata','masterLibraryCounts.csv', package='ACER'),
                          countFile = system.file('extdata','countData.csv', package='ACER'),
                          negCtrlFile = system.file('extdata','negCtrlGenes.txt', package='ACER'), 
                          sampleInfoFile=system.file('extdata','sampleAnnotations.txt', package='ACER'),
                          hasInitSeq = T)
newModelObj <- ModelObj$new(user_DataObj = newDataObj,
                            use_neg_ctrl=T,
                            test_samples='test',
                            use_master_library = T)
newResultsObj <- optimizeModelParameters(user_DataObj = newDataObj,
                                         user_ModelObj = newModelObj)
writeResObj(newResultsObj)

References

[1] Hutton, E. R., Vakoc, C. R., and Siepel, A. (2020). ACE: A Probabilistic Model for Characterizing Gene-Level Essentiality in CRISPR Screens. bioRxiv, https://www.biorxiv.org/content/10.1101/868919v2