crest is a simple-version in-house pipeline for CREST-seq analysis which requires R, R packages (locfit, stringr, edgeR, GenomicRanges), samtools (1.2), python.
| Dependency | URL |
|---|---|
| R | https://www.r-project.org/ |
| locfit (R) | https://www.bioconductor.org/packages/release/bioc/html/flowFit.html |
| stringr (R) | https://cran.r-project.org/web/packages/stringr/vignettes/stringr.html |
| edgeR (R) | https://bioconductor.org/packages/release/bioc/html/edgeR.html |
| GenomicRanges (R) | https://bioconductor.org/packages/release/bioc/html/GenomicRanges.html |
| samtools (1.2) | https://sourceforge.net/projects/samtools/files/samtools/1.2/ |
| python (2.7) | https://www.python.org/download/releases/2.7/ |
The installation contains the following steps:
- [clone] - clone the repertoire
git clone https://github.com/r3fang/crest.git- [compile] - compile RRA and other programs
if [ -f ./bin/RRA ]; then
rm ./bin/RRA
fi
chmod +x ./bin/*
cd rra; make; cd ..;- [path] - add the ./bin folder to .bash_profile
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
echo "export PATH=\$PATH:$DIR/bin" >> ~/.bash_profile
bash ~/.bash_profile
- [samtools] - install samtools if not installed
command -v samtools >/dev/null 2>&1 || {
wget https://github.com/samtools/samtools/releases/download/1.2/samtools-1.2.tar.bz2;
tar -vxjf samtools-1.2.tar.bz2;
cd samtools-1.2;
make;
cd ..;
cp samtools-1.2/samtools ./bin/;
rm samtools-1.2.tar.bz2
}- [R packages] - install R packages
# install locfit
wget https://cran.r-project.org/src/contrib/locfit_1.5-9.1.tar.gz
R CMD INSTALL --clean -l $R_LIBS locfit_1.5-9.1.tar.gz
# install stringr and its dependencies
wget https://cran.r-project.org/src/contrib/magrittr_1.5.tar.gz
R CMD INSTALL --clean -l $R_LIBS magrittr_1.5.tar.gz
wget https://cran.r-project.org/src/contrib/stringr_1.0.0.tar.gz
R CMD INSTALL --clean -l $R_LIBS stringr_1.0.0.tar.gz
# install edgeR
wget https://bioconductor.org/packages/release/bioc/src/contrib/edgeR_3.14.0.tar.gz
R CMD INSTALL --clean -l $R_LIBS edgeR_3.14.0.tar.gz
# install GenomicRanges and its depednencies (or use bioconductor)
wget https://bioconductor.org/packages/release/bioc/src/contrib/zlibbioc_1.18.0.tar.gz
wget http://bioconductor.org/packages/3.1/bioc/src/contrib/BiocGenerics_0.14.0.tar.gz
wget http://bioconductor.org/packages/3.1/bioc/src/contrib/XVector_0.8.0.tar.gz
wget http://bioconductor.org/packages/3.1/bioc/src/contrib/GenomicRanges_1.20.8.tar.gz
R CMD INSTALL --clean -l $R_LIBS BiocGenerics_0.14.0.tar.gz
R CMD INSTALL --clean -l $R_LIBS zlibbioc_1.18.0.tar.gz
R CMD INSTALL --clean -l $R_LIBS XVector_0.8.0.tar.gz
R CMD INSTALL --clean -l $R_LIBS GenomicRanges_1.20.8.tar.gz$ crest
Program: crest (CREST-seq analysis pipeline Ren Lab)
Version: v04.17.2017
Contact: Rongxin Fang <r3fang@ucsd.edu>
URL: https://github.com/r3fang/crest
usage: crest [-h] [-i INPUT] [-t T1,T2,T3] [-c C1,C2,C3] [-r chr6:30132134-32138339] [-o PREFIX] [-m 5] [-s 50] [-n 3] [-p 0.05] [-l 1000]
Example:
crest -i data/data.txt -t T1,T2,T3,T4,T5 -c C1,C2 -r chr6:30132134-32138339 -o demo -g hg19
Options:
-- Required:
-i STR input crest-standard matrix.
-t STR treatment sample IDs, seperated by comma without space.
-c STR control sample IDs, seperated by comma without space.
-r STR region that CREST-seq performed against (e.g. chr1:1-100).
-o STR prefix of outout files.
-- Optional:
-m INT sgRNA pairs with CPM (count per million) smaller than [3]
will be filtered before peak calling.
-s INT screened region -r will be splitted into bins of [50] bp.
-n INT a bin is considered significant with at least [3] pairs span it.
-p FLOAT score cutoff for a significant bin [0.1].
-l INT a peak will be extended to [1000] bp if shorter .
Note: To use crest, please be sure that the input matrix is in the required format.
Check if your input is crest-required format: 'crest_input_check -i data/data.txt'
Diao Y*, Fang R.*, Li B.*, Meng Z., Yu J., Qiu Y., Lin K., Huang H., Liu T., Marina R.J., Jung I., Shen Y., Guan K., Ren B. A tiling-deletion-based genetic screen for cis-regulatory element identification in mammalian cells. Nature Methods (2017) doi:10.1038/nmeth.4264 (* contributed equally)
MIT