A comprehensive pipeline for Ribo-seq data analysis (mapping, quantification, and visualization).
PipeRiboseq has been used in the following publication:
Sun, Y.H., Zhu, J., Xie, L.H. et al. Ribosomes guide pachytene piRNA formation on long intergenic piRNA precursors. Nat Cell Biol 22, 200–212 (2020). https://doi.org/10.1038/s41556-019-0457-4
This pipeline is designed to run on Linux servers, and requires the following software:
R
Python3
STAR
bowtie2
bedtools
samtools
salmon
FeatureCounts (from Subread)
fastqc (optional)
cufflinks (optional)
ribotish (requires Python3, for Ribo-seq QC. Better to have it)
The above software can also be installed using conda, as below:
#Create piperiboseq environment, ~15-20min
conda create --name piperiboseq
conda install -n piperiboseq -c bioconda ribotish #Install ribotish first
conda install -n piperiboseq -c conda-forge r-base #Will take a while to solve env
conda install -n piperiboseq -c bioconda bowtie2
conda install -n piperiboseq -c bioconda star
conda install -n piperiboseq -c bioconda bedtools
conda install -n piperiboseq -c bioconda samtools
conda install -n piperiboseq -c bioconda subread
conda install -n piperiboseq -c bioconda fastqc
conda install -n piperiboseq -c bioconda git
#We ignore cufflinks since we usually don't need it.
#Alternatively, you can create the env using the yml file provided:
conda env create --name piperiboseq --file=conda_env_Linux_piperiboseq.yml #For Linux
conda env create --name piperiboseq --file=conda_env_MacOS_piperiboseq.yml #For MacOS
#This environment is not compatible with salmon, so we have to download salmon and install it separately:
wget "https://github.com/COMBINE-lab/salmon/releases/download/v1.9.0/salmon-1.9.0_linux_x86_64.tar.gz"
tar -xvzf salmon-1.9.0_linux_x86_64.tar.gz
#Finally, add the salmon-1.9.0_linux_x86_64/bin directory to PATH:
PATH=$PATH:/path/to/salmon-1.9.0_linux_x86_64/bin
#Create another env for multiqc, due to the conflict with piperiboseq:
conda create --name multiqc_env
conda install -n multiqc_env -c bioconda multiqc
The main pipeline script is PipeRiboseq.sh, and dependencies are in the ./bin folder.
Also, for Mac OS, manually set the pipeline home directory at PipeRiboseq.sh line 58 manually,
because the 'readlink' command does not work for MacOS:
HomeDir="/Users/yusun/Downloads/PipelineHomeDir"
For mm10 (mouse) and hg38 (human), some files have been provided. If you have installed PipeRNAseq or PipeSmRNAseq pipeline before, then the folders such as the bin, genome folders (mm10, hg38, etc.) are compatible and many files can be shared.
Activate the env if you use conda:
conda activate piperiboseq
Here is an example of mm10 genome setup.
1, Download scripts from GitHub to a Linux server:
git clone https://github.com/sunyumail93/PipeRiboseq.git
mv PipeRiboseq PipelineHomeDir
#Also, add PipelineHomeDir and the associated bin folder to PATH so
pipeline scripts (including PipeRiboseq.sh) can be recognized:
PATH=$PATH:/path/to/PipelineHomeDir:/path/to/PipelineHomeDir/bin
2, Set up index files for genome mapping
2a, Download whole genome fasta sequence and chromosome sizes from UCSC goldenpath:
cd PipelineHomeDir/mm10/Sequence
wget http://hgdownload.cse.ucsc.edu/goldenPath/mm10/bigZips/mm10.fa.gz
gunzip *.gz
wget "http://hgdownload.cse.ucsc.edu/goldenPath/mm10/bigZips/mm10.chrom.sizes" -O mm10.ChromInfo.txt
2b, Extract RNA sequences
#Go to PipelineHomeDir/mm10/Annotation
cd ../Annotation
gunzip *.gz
cd ../Sequence
bedtools getfasta -s -split -name -fi mm10.fa -bed ../Annotation/mm10.RefSeq.reduced.bed12 -fo mm10.RefSeq.reduced.bed12.fa.t
cat mm10.RefSeq.reduced.bed12.fa.t|sed 's/::.*//' > mm10.RefSeq.reduced.bed12.fa
rm -rf mm10.RefSeq.reduced.bed12.fa.t
2c, Set up index files:
#Create PipelineHomeDir/mm10/Index, and go to the Index directory
cd ../
mkdir Index
cd Index
#STAR index:
mkdir STARIndex
#After creating the above folder, run the following index-building command directly in PipelineHomeDir/mm10/Index
#Do not cd into the STARIndex folder
#This will take ~1h using the 64G memory, 8 CPUs. Better to run it on HPC:
STAR --runMode genomeGenerate --genomeDir STARIndex --genomeFastaFiles ../Sequence/mm10.fa --sjdbGTFfile ../Annotation/mm10.RefSeq.reduced.bed12.geneid.gtf --sjdbOverhang 100
#salmon index (SalmonIndex directory will be created automatically):
#Genome FASTA index fai file will also be generated
salmon index -t ../Sequence/mm10.RefSeq.reduced.bed12.fa -i SalmonIndex
#miRNA and rRNA bowtie2 index:
mkdir miRNAIndex
mkdir rRNAIndex
bowtie2-build ../Sequence/mm10.rRNA.fa ./rRNAIndex/rRNAIndex
bowtie2-build ../Sequence/mm10.miRNA.fa ./miRNAIndex/miRNAIndex
3, Compile the C++ program if necessary
The FastqAdapterTimmer binary file was compiled on a Linux system. It may need to be compiled again:
#Check if the compiled file is working or not. Go to PipelineHomeDir/bin:
cd ../../bin
chmod +x FastqAdapterTimmer
./FastqAdapterTimmer
#If you encountered an error after running the above command, then compile it:
g++ FastqAdapterTimmer.cpp -o FastqAdapterTimmer
4, Add executable permissions for files under PipelineHomeDir/
#Go to PipelineHomeDir/
cd ../
#Add permission to files
chmod +x PipeRiboseq.sh
chmod +x ./bin/FastqAdapterTimmer
chmod +x ./bin/faSize
chmod +x ./bin/bedGraphToBigWig
chmod +x ./bin/bigWigToBedGraph
chmod +x ./bin/*sh
chmod +x ./bin/*py
Three UCSC tools (from http://hgdownload.soe.ucsc.edu/admin/exe/) are used: faSize, bedGraphToBigWig, and bigWigToBedGraph. If the binary files in the ./bin folder are not working (After chmod +x, then execute ./bin/bedGraphToBigWig but get errors), please re-download them by choosing the correct version (e.g. linux.x86_64). It would be better to check this manually before running the pipeline.
PipelineHomeDir/
├── PipeRiboseq.sh
├── bin/
└── mm10/
└── Annotation/
├── mm10.RefSeq.reduced.bed12
├── mm10.RefSeq.reduced.mRNA.bed12
├── mm10.RefSeq.reduced.bed12.geneid.gtf
└── mm10.uniqMatching.txt
└── Index/
├── miRNAIndex/
├── rRNAIndex/
├── SalmonIndex/
└── STARIndex/
└── Sequence/
├── mm10.fa
├── mm10.fai
├── mm10.ChromInfo.txt
├── mm10.miRNA.fa
├── mm10.rRNA.fa
└── mm10.RefSeq.reduced.bed12.fa
└── hg38/
...
Notes:
This repository has prepared the files for mm10 and hg38. If you are working on other genomes, some critical files need to be prepared. For more information, see this tutorial.
1, For the Annotation folder, download GTF file from the UCSC table browser. reduced: Only one location was chosen when one gene duplicates at multiple genomic loci.
2, uniqMatching.txt file contains one-to-one matching from transcript to gene name. This can be extracted from the GTF file.
3, For the Index folder, indexes are not included in this GitHub directory, but need to be created during set up. Please make sure the same STAR version is used to build the index and run the pipeline.
4, For the Sequence folder, RefSeq.reduced.bed12.fa was converted from RefSeq.reduced.bed12 file using bedtools, and rRNA genes (rRNA affects salmon quantification TPM) have been removed. genome.fa and ChromInfo.txt files need to be downloaded from UCSC goldenpath. The fai index file is not required now since it will be generated by samtools when needed.
Type the pipeline name, then you will see the manual page:
PipeRiboseq.sh
Manual page:
The trimming script also has a manual page:
FastqAdapterTimmer
A regular run using mostly default parameters:
PipeRiboseq.sh -i Data.fastq.gz -g mm10 -normCDS
More parameters used, and plot given genes in the list file (mRNAs in the list file must be Refseq mRNA ID: NM_xxx):
PipeRiboseq.sh -i Data.fastq.gz -g mm10 -noqc -noriboqc -p 4 -normCDS -m 3 -plotRNA list
The demo fastq file is in PipelineHomeDir/Demo/Demo.trimmed.fastq.gz, which is a small fraction of the public dataset GEO SRA: SRR989509.
Run the demo to test the pipeline. This will finish in ~10min:
#If using conda, activate the env first:
conda activate piperiboseq
PipeRiboseq.sh -i Demo.trimmed.fastq.gz -g mm10 -p 4 -normCDS
1, Download data
Use a public dataset: GEO SRA: SRR989509
fastq-dump is part of NCBI SRA Toolkit:
fastq-dump --split-3 SRR989509
2, Trim adaptor using the trimming script from /bin repository: FastqAdapterTimmer
FastqAdapterTimmer -i SRR989509.fastq -a CTGTAG -o Data.trimmed.fastq
gzip Data.trimmed.fastq
3, Run Ribo-seq pipeline:
PipeRiboseq.sh -i Data.trimmed.fastq.gz -g mm10 -p 4 -normCDS
1, Length distribution of Ribo-seq mapped reads:
2, Ribo-seq corrected 5´-ends around top expressed mRNAs' AUG:
3, Ribo-seq corrected 5´-ends around top expressed mRNAs' STOP codon:
4, An example of individual gene visualization:
5, Ribo-seq QC by RiboTISH:
