riboprofiling_pipeline_arthur's Introduction

Arthur's pipeline for mapping ribo-profiling reads

generate bam files from fastq.gz files

dependency

python (>= 3.6.8),
cutadapt (>= 2.1),
umi_tools (>= 0.5.5),
bowtie (>= 1.2.2)

installation

download the repository

cd PATH/TO/THE/REPOSITORY
conda env create -f ribo_profiling_pipeline_env.yml   #create the appropriate environment for the pipeline
chmod 755 codes/*   # make all the scripts executable
chmod run_pipeline.sh   # make all the scripts executable

example

activate the environment we created

source activate ribo_profiling

create the bowtie reference according to http://bowtie-bio.sourceforge.net/manual.shtml#the-bowtie-build-indexer
or download pre-computed reference from ftp://ftp.ccb.jhu.edu/pub/data/bowtie_indexes/

run the pipeline by

PATH/TO/run_pipeline.sh $Input $Output $Thread $Bowtie_ref

Input = the path to your input fastq.gz file
Output = the path to your output directory
Thread = an integer larger than 0 indicates how many thread you want to use
Bowtie_ref = the path to your bowtie reference file, same as what you will use for bowtie

for example:

~/tools/Riboprofiling_pipeline_Arthur/run_pipeline.sh 190321_Bcell/B_cell_R1.fastq.gz 190321_out/ 4 /home/software/bowtie-1.1.1/genomes/mm10_150921/mm10_150921

inspired by codes from Vince Harjono (Zid lab UCSD)
library prep protocol modified from: McGlincy, N. J., & Ingolia, N. T. (2017). Transcriptome-wide measurement of translation by ribosome profiling. Methods, 126, 112-129.

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