Biowulf High Performance Computing at the NIH
RSEM on Biowulf

RSEM is a software package for estimating gene and isoform expression levels from RNA-Seq data. The RSEM package provides an user-friendly interface, supports threads for parallel computation of the EM algorithm, single-end and paired-end read data, quality scores, variable-length reads and RSPD estimation. In addition, it provides posterior mean and 95% credibility interval estimates for expression levels. For visualization, It can generate BAM and Wiggle files in both transcript-coordinate and genomic-coordinate. Genomic-coordinate files can be visualized by both UCSC Genome browser and Broad Institute’s Integrative Genomics Viewer (IGV). Transcript-coordinate files can be visualized by IGV. RSEM also has its own scripts to generate transcript read depth plots in pdf format. The unique feature of RSEM is, the read depth plots can be stacked, with read depth contributed to unique reads shown in black and contributed to multi-reads shown in red. In addition, models learned from data can also be visualized. Last but not least, RSEM contains a simulator.

References:

Documentation
Important Notes

Based on the tutorial https://github.com/bli25ucb/RSEM_tutorial

The following steps were already finished on our systems. User can use the index files in the shared area. Some of the steps can not be run by users due to permission setting.

Biowulf > $ mkdir /fdb/rsem  ## users do now have permission to do the following steps in /fdb/rsem but can create directory under personal space such as /data/$USER and replace the following /fdb/rsem with the directory created.

Biowulf > $ sinteractive --mem=10g
cn1234 > $ module load rsem
cn1234 > $ cd /fdb/rsem
cn1234 > $ ln -s /fdb/ensembl/pub/release-82/fasta/mus_musculus/dna/Mus_musculus.GRCm38.dna.toplevel.fa  Mus_musculus.GRCm38.dna.toplevel.fa
cn1234 > $ ln -s /fdb/ensembl/pub/release-82/gtf/mus_musculus/Mus_musculus.GRCm38.82.chr.gtf  Mus_musculus.GRCm38.82.chr.gtf

Build reference from genome (Users can use the reference directly without building) :
cn1234 > $ rsem-prepare-reference --bowtie2 --gtf Mus_musculus.GRCm38.82.chr.gtf Mus_musculus.GRCm38.dna.toplevel.fa ref_from_genome/mouse_ref

Build reference from ensemble transcripts (Users can use the reference directly without building) :
Downloade mouse_ref_building_from_transcripts.tar.gz from https://www.dropbox.com/s/ie67okalzaw8zzj/mouse_ref_building_from_transcripts.tar.gz?dl=0
cn1234 > $ tar xvfz mouse_ref_building_from_transcripts.tar.gz
This created two files: mouse_ref.fa and mouse_ref_mapping.txt

cn1234 > $ rsem-prepare-reference --transcript-to-gene-map mouse_ref_mapping.txt --bowtie2 mouse_ref.fa ref_from_transcripts/mouse_ref

 

Interactive job
Interactive jobs should be used for debugging, graphics, or applications that cannot be run as batch jobs.

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive
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 ~]$ module load rsem bowtie STAR
[user@cn3144 ~]$ rsem-calculate-expression -p 2 --paired-end --bowtie2 \
				 --estimate-rspd --append-names --output-genome-bam \
				/data/maoj/rsem/SRR937564_1.fastq /data/maoj/rsem/SRR937564_2.fastq \
				/fdb/rsem/ref_from_genome/mouse_ref_CRCh38.82 LPS_6h
[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

Batch job
Most jobs should be run as batch jobs.

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

#!/bin/bash

module load rsem  bowtie  STAR
cd /data/$USER/dir
rsem-calculate-expression -p $SLURM_CPUS_PER_TASK --temporary-folder /lscratch/$SLURM_JOBID/tempdir \
--paired-end --bowtie2 --estimate-rspd --append-names --output-genome-bam SRR937564_1.fastq SRR937564_2.fastq \
/fdb/rsem/ref_from_genome/mouse_ref LPS_6h

Submit this job using the Slurm sbatch command.

sbatch --cpus-per-task=4 --mem=10g --gres=lscratch:100 rsem.sh

For multiple threaded job, such as -p used in rsem-calculate-expression, use '--cpus-per-task' on the command line and the $SLURM_CPUS_PER_TASK will be assigned automatically to the number user assigned (4 in this case).

To use temporary local space, use "--gres=lscratch:XXX" which will allocate XXX gb of space for the job. The space can be accessed by using "/lscratch/$SLURM_JOBID/directoryNameYouChoose" as shown in the script.

For more memory requirement (default 2xcpus=8gb in this case), use --mem flag

Swarm of Jobs
A swarm of jobs is an easy way to submit a set of independent commands requiring identical resources.

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


  cd /data/$USER/dir1; rsem command1; rsem command2
  cd /data/$USER/dir2; rsem command1; rsem command2
  cd /data/$USER/dir3; rsem command1; rsem command2

Submit this job using the swarm command.

swarm -f swarmfile -t 4 --module rsem,bowtie,STAR
where
-g # Number of Gigabytes of memory required for each process (1 line in the swarm command file)
-t # Number of threads/CPUs required for each process (1 line in the swarm command file).
--module rsem Loads the rsem module for each subjob in the swarm