CRISPR Pooled Screen Analysis using Beta-Binomial Test

Provides functions for hit gene identification and quantification of sgRNA (single-guided RNA) abundances for CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) pooled screen data analysis. Details are in Jeong et al. (2019) and Baggerly et al. (2003) .

CB2(CRISPRBetaBinomial) is a new algorithm for analyzing CRISPR data based on beta-binomial distribution. We provide CB2 as a R package, and the interal algorithms of CB2 are also implemented in CRISPRCloud.

How to install

Currently CB2 is now on CRAN, and you can install it using install.package function.


Installation Github version of CB2 can be done using the following lines of code in your R terminal.


Alternatively, here is a one-liner command line for the installation.

Rscript -e "install.packages('devtools'); devtools::install_github('LiuzLab/CB2')"

A simple example how to use CB2 in R

FASTA <- system.file("extdata", "toydata",
                     package = "CB2")
df_design <- data.frame()
for(g in c("Low", "High", "Base")) {
  for(i in 1:2) {
    FASTQ <- system.file("extdata", "toydata",
                         sprintf("%s%d.fastq", g, i), 
                         package = "CB2")
    df_design <- rbind(df_design, 
        group = g, 
        sample_name = sprintf("%s%d", g, i),
        fastq_path = FASTQ, 
        stringsAsFactors = F)
sgrna_count <- run_sgrna_quant(FASTA, df_design)
sgrna_stat <- run_estimation(sgrna_count$count, df_design, "Base", "Low")
gene_stat <- measure_gene_stats(sgrna_stat)


Reference manual

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1.2.1 by Hyun-Hwan Jeong, a month ago

Browse source code at

Authors: Hyun-Hwan Jeong [aut, cre]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Rcpp, metap, magrittr, dplyr, tibble, stringr, ggplot2, tidyr, glue, pheatmap

Suggests testthat, knitr, rmarkdown

Linking to Rcpp, RcppArmadillo

See at CRAN