crisprCHOPOFF: R wrapper for CHOPOFF, a CRISPR OFF target search algorithm

This package is under heavy development to include more features.

About

Efficient search of CRISPR OFF targets

Installation

Package is available here on github (Experimental branch, R version >= 4.1.0)

if (!requireNamespace("remotes", quietly=TRUE))
    install.packages("remotes")
remotes::install_github("JokingHero/crisprCHOPOFF)

System requirements

OS support: Unix (linux & mac) For windows, run through WSL (windows subsystem for linux)

Normally, the first time running build_index(), the backend will be installed for you, through the function install_CHOPOFF()

# The script ran, can be found from:
system.file("bash_script", "install_julia_and_CHOPOFF.sh", package = "crisprCHOPOFF")

install_CHOPOFF()

For direct install into ~/bin, copy and run code below, it will install:

Julia 1.8.5
CHOPOFF.jl The script content is this:

# In Shell
# Get julia 1.8.5 (required version)
mkdir -p ~/bin/julia
cd ~/bin/julia
wget https://julialang-s3.julialang.org/bin/linux/x64/1.8/julia-1.8.5-linux-x86_64.tar.gz
tar -xvzf julia-1.8.5-linux-x86_64.tar.gz
# Update PATH and source .bashrc
echo 'export PATH="$PATH:~/bin/julia/julia-1.8.5/bin"' >> ~/.bashrc
echo 'export JULIA_NUM_THREADS=11' >> ~/.bashrc
. ~/.bashrc # resource shell
# Clone julia CHOPOFF library (select folder where you have your github clones)
cd ~/bin # update path to your path if needed
git clone git@github.com:JokingHero/CHOPOFF.jl.git
cd CHOPOFF.jl
./build_standalone.sh
# In .bashrc (update to your custom path!)
echo 'export PATH="$PATH:~/bin/CHOPOFF.jl/build/bin/"' >> ~/.bashrc
# In Shell
. ~/.bashrc # resource shell
echo CHOPOFF=~/bin/CHOPOFF.jl/build/bin/CHOPOFF >> ~/.Renviron
# <- To allow RSTUDIO to see the CHOPOFF path, then restart RSTUDIO

CHOPOFF should now be ready to use in the R wrapper

If you already have julia and CHOPOFF installed, you only need to make sure CHOPOFF is in .Renviron.

echo CHOPOFF=~/bin/CHOPOFF.jl/build/bin/CHOPOFF >> ~/.Renviron

More information

After installation run:

library(crisprCHOPOFF)

# Build a genome index to search against
?build_index

# Search the index with selected guides
?search_index

Quick walk-through:

name <- "CAS9"
genome <- system.file("extdata/sample_genome", "semirandom.fa", package = "crisprCHOPOFF")
## Note: a fasta index ".fai" file must exist in directory of genome.
# You can make it with:
#if (!file.exists(paste0(genome, ".fai"))) {
#Rsamtools::indexFa(genome)
#}
out_dir_index <- file.path(tempdir(), "CHOPOFF_sample_genome")
build_index(name, genome, out_dir_index, validate = FALSE, distance = 2)

# Now search some guides
guides <- system.file("extdata/sample_genome", "guides.txt", package = "crisprCHOPOFF")
# Quick preview in guides:
guide_candidates <- read.table(guides, col.names = "guides")
unique(nchar(unlist(guide_candidates))) # Unique lengths of guides
guide_hits <- search_index(guides, out_dir_index, validate = FALSE, distance = 2)
guide_hits_table <- read.table(guide_hits, sep = ",", header = TRUE)
# use data.table::fread for reading in large list
# Subset to 0 distance hits
dist0 <- guide_hits_table[guide_hits_table$distance == 0,]
head(dist0)
# Which chromosomes is a specific guide found on with 0 distance hits?
unique(dist0[dist0$guide == "TCCGGCCTGGTTATCGAAGG",]$chromosome) # 2 chromosomes

Please read Bioconductor vignettes for detailed tutorials and examples.

Feedback

Please feel free to provide feedback or desired functionality by creating a new issue on our github page.