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Build Status PyPI version GitHub license

HTSeqCountCluster

A cli wrapper for running htseq's htseq-count on a cluster.

View a project overview at our Datasnakes site.

Install

pip install HTSeqCountCluster

Features

  • For use with large datasets (we've previously used a dataset of 120 different human samples)
  • For use with SGE/SGI cluster systems
  • Submits multiple jobs
  • Command line interface/script
  • Merges counts files into one counts table/csv file
  • Uses accepted_hits.bam file output of tophat

Examples

Run htseq-count-cluster

After generating bam output files from tophat, instead of using HTSeq's htseq-count, you can use our htseq-count-cluster script. This script is intended for use with clusters that are using pbs (qsub) for job monitoring.

Our default htseq-count command is htseq-count -f bam -s no file.bam file.gtf -o htseq.out. This command does not take into account any strandedness (-s no) for the input bamfiles (-f bam) and uses the default union mode. For the default mode union, only the aligned read determines how the read pair is counted.

htseq-count-cluster -p path/to/bam-files/ -f samples.csv -g genes.gtf -o path/to/cluster-output/
Argument Description Required
-p This is the path of your .bam files. Presently, this script looks for a folder that is the sample name and searches for an accepted_hits.bam file (tophat output). Yes
-i You should have a csv file list of your samples or folder names (no header). Yes
-g This should be the path to your genes.gtf file. Yes
-o This should be an existing directory for your output counts files. Yes
-e    

This script uses logzero so there will be color coded logging information to your shell.

A common linux practice is to use screen to create a new shell and run a program so that if it does produce output to the stdout/shell, the user can exit that particular shell without the program ending and utilize another shell.

Help message output for htseq-count-cluster
usage: htseq-count-cluster [-h] -p INPATH -f INFILE -g GTF -o OUTPATH
                              [-e EMAIL]

This is a command line wrapper around htseq-count.

optional arguments:
  -h, --help            show this help message and exit
  -p INPATH, --inpath INPATH
                        Path of your samples/sample folders.
  -f INFILE, --infile INFILE
                        Name or path to your input csv file.
  -g GTF, --gtf GTF     Name or path to your gtf/gff file.
  -o OUTPATH, --outpath OUTPATH
                        Directory of your output counts file. The counts file
                        will be named.
  -e EMAIL, --email EMAIL
                        Email address to send script completion to.

*Ensure that htseq-count is in your path.
Merge output counts files

In order to prep your data for DESeq2, limma or edgeR, it's best to have 1 merged counts file instead of multiple files produced from the htseq-count-cluster script. We offer this as a standalone script as it may be useful to keep those files separate.

merge-counts -d path/to/cluster-output/
Help message for merge-counts
usage: merge-counts [-h] -d DIRECTORY

Merge multiple counts tables into 1 counts .csv file.

Your output file will be named:  merged_counts_table.csv

optional arguments:
  -h, --help            show this help message and exit
  -d DIRECTORY, --directory DIRECTORY
                        Path to folder of counts files.

ToDo

  • [ ] Monitor jobs.
  • [ ] Enhance wrapper input for other use cases.
  • [ ] Add example data.

Maintainers

Shaurita Hutchins | @sdhutchins | ✉
Rob Gilmore | @grabear | ✉

Help

Please feel free to open an issue if you have a question/feedback/problem or submit a pull request to add a feature/refactor/etc. to this project.

Citation

Simon Anders, Paul Theodor Pyl, Wolfgang Huber;HTSeq—a Python framework to work with high-throughput sequencing data, Bioinformatics, Volume 31, Issue 2, 15 January 2015, Pages 166–169,https://doi.org/10.1093/bioinformatics/btu638