CSSA-package: CSSA: Analysis and Simulation Tools for CRISPR-Cas9 Pooled...
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CSSA-package

R Documentation

CSSA: Analysis and Simulation Tools for CRISPR-Cas9 Pooled Screens

Description

CSSA contains a number of functions to analyze and simulation pooled CRISPR-Cas9-based screens. The simulators, represented by the CRISPRsim and sortingsim functions, offer an easy but also highly customizable tool to create data with guide- and gene-specific variables that can be randomly assigned or specified by the user. The analysis tools currently contain functions to calculate rate ratios, odds based on nonparametric guide distribution, a function to combine genewise Z-values or odds, and a function that calculates effect sizes of gene knockout and guide efficacy based on rate ratios and duration of the experiment.

CSSA functions

CRISPRsim: Simulate a CRISPR-Cas9 pooled screen
radjust: Calculate rate ratios restricted by confidence level
nestedradjust: Calculate rate ratios of rate ratios restricted by confidence level
jar: Rate ratios after adding an artificial number to all features
doublejar: Rate ratios of rate ratios after adding an artificial number to all features
r2Z: Convert rate ratios to Z-values
sumZ: Calculate corrected summed Z-values per gene
getdeg: Derive growth-modifying effect of gene knockout in pooled experiments
ess: Get a list of essential genes or corresponding indices in the data set
noness: Get a list of nonessential genes or corresponding indices in the data set
sortingsim: Simulate a selection-based CRISPR-Cas9 pooled screen
oddscores: Calculate odds per guide
geneodds: Calculate odds per gene
odds2pq: Calculate p-values and q-values for odds
geteffect: Approximate effect of gene knockout on growth
rrep: Calculate rate ratios with standard error of count data based on replicates
degrep: Derive growth-modifying effect of gene knockout in pooled experiments with replicate arms