TopHat is a splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to mammalian-sized genomes using the short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons.

References:

• Cole Trapnell, L. Pachter L, and S. L. Salzberg. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 2009, 25:1105-1111
• Daehwan Kim, G. Pertea, C. Trapnell, H. Pimentel, R. Kelley, S. L. Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology 2013, 14:R36.
• Daehwan Kim, and S. L. Salzberg. TopHat-Fusion: an algorithm for discovery of novel fusion transcripts. Genome Biology 2011, 12:R72.

Please note that TopHat has entered a low maintenance, low support stage as it is now largely superseded by HISAT2 which provides the same core functionality (i.e. spliced alignment of RNA-Seq reads), in a more accurate and much more efficient way.

• Home page
• Manual
• Google group

• Module Name: tophat (see the modules page for more information)
• Multithreaded
• Environment variables set
  • PATH

TopHat makes use of either bowtie2 (the default) or bowtie (optional; necessary for colorspace reads as bowtie2 does not support colorspace). TopHat is limited to a maximal read length of 1024nts.

TopHat2 now includes TopHat-Fusion's ability to look for fusions between different transcripts (--fusion-search).

TopHat will need either bowtie2 or bowtie indices which are available as part of the igenomes package at

/fdb/igenomes/[organism]/[source]/[build]/Sequence/Bowtie[2]Index/*

• [organism] is the specific organism of interest (Gallus_gallus, Rattus_norvegicus, etc.)
• [source] is the source for the sequence (NCBI, Ensembl, UCSC)
• [build] is the specific genome build of interest (hg19, build37.2, GRCh37)

More information on the locally available igenomes builds/organisms is available from our scientific database index. For more information about igenomes in general, iGenomes readme.

Allocate an interactive session and run the program.
Sample session (user input in bold):

[user@biowulf]$ sinteractive --cpus-per-task=8 --mem=10g
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ~]$ cd /data/$USER/test_data
[user@cn3144 ~]$ module load tophat
[user@cn3144 ~]$ tophat -o job1 -p8 /path/to/genome /path/to/fastq.gz
...
[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

Create a batch input file (e.g. tophat.sh). For example:

#! /bin/bash
module load tophat
cd /data/${USER}/test_data
tophat \
  --output-dir=./tophat_test \
  --min-anchor-length=10 \
  --num-threads=$SLURM_CPUS_PER_TASK \
  --b2-sensitive \
  /fdb/igenomes/Mus_musculus/UCSC/mm9/Sequence/Bowtie2Index/genome \
  fastq/rnaseq_500k.fastq.gz

Submit this job using the Slurm sbatch command.

sbatch --cpus-per-task=16 --mem=20g tophat.sh

Note that tophat by default creates a ouput directory called tophat_out. Therefore, to run multiple jobs in parallel, the jobs either have to be run in separate directories or the command line has to specify the -o / --output_dir for each job.

Create a swarmfile (e.g. tophat.swarm). For example:

tophat -o job1 -p ${SLURM_CPUS_PER_TASK} --b2-sensitive \
  --GTF=annot/140609_refseq_nomir_nosnor.gtf --no-novel-juncs \    
  /fdb/igenomes/Mus_musculus/UCSC/mm9/Sequence/Bowtie2Index/genome \
  fastq/rnaseq_500k.fastq.gz
tophat -o job2 -p ${SLURM_CPUS_PER_TASK} --b2-sensitive \
  --GTF=annot/140609_refseq_nomir_nosnor.gtf --no-novel-juncs \    
  /fdb/igenomes/Mus_musculus/UCSC/mm9/Sequence/Bowtie2Index/genome \
  fastq/rnaseq_250k.fastq.gz

Submit this job using the swarm command.

swarm -f tophat.swarm -g 10 -t 16 --module tophat