TransDecoder
TransDecoder finds candidate coding regions in transcript sequences, such as transcripts assembled de novo with Trinity or from RNA-seq alignments to a genome. It predicts the protein sequences of the transcripts, which you can then annotate with Trinotate.
License
Free to use and open source under the BSD 3-Clause License.
Available
- Roihu-CPU: 5.7.1, via the
bio-appsmodule.
Usage
TransDecoder is part of the bio-apps collection on Roihu. Load the bio-apps module tree and then the TransDecoder module:
TransDecoder runs in two steps. First, find the long open reading frames (ORFs) in the transcripts. Then, predict which of them are likely coding regions:
The predicted proteins are written to transcripts.fasta.transdecoder.pep, their
coding sequences to transcripts.fasta.transdecoder.cds, and their locations to
transcripts.fasta.transdecoder.gff3 and .bed. By default, ORFs must be at least
100 amino acids long (-m). For strand-specific data, add -S to
TransDecoder.LongOrfs to search only the top strand of the transcripts.
To keep ORFs that have Pfam domain or BLAST hits even if they would otherwise be
left out, give the search results to TransDecoder.Predict with --retain_pfam_hits
and --retain_blastp_hits. See the
TransDecoder documentation for
details.
Example batch script
#!/bin/bash
#SBATCH --job-name=transdecoder
#SBATCH --account=<project>
#SBATCH --output=output_%j.txt
#SBATCH --error=errors_%j.txt
#SBATCH --partition=small
#SBATCH --time=04:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem=8G
module load bio-apps/v202603
module load transdecoder/5.7.1
TransDecoder.LongOrfs -t transcripts.fasta
TransDecoder.Predict -t transcripts.fasta
Replace <project> with your CSC project (for example project_2001234).
See creating a batch job script for Roihu for more information about running batch jobs.