howto:bioinformatics
This is an old revision of the document!
Table of Contents
Bioinformatics at the CHPC
the old version of this page can be found here
While THIS MESSAGE is here, please consider THIS PAGE as a work in progress.
Welcome to the bioinformatics at the CHPC wiki page! This page describes the basic procedures involved in getting your programs running at the CHPC rather than a description of how to do any particular bioinformatics analysis. If anything is unclear please hover your mouse over the superscripts! 1) For the most part we will be assuming you have at least a little familiarity with Linux. Much of this information is available elsewhere in the CHPC's wiki (probably in more detail), but here we are trying to have everything accessible in one place for the bioinformatics community. Please do read the quick start guide before continuing and pay special attention to the sections on queues and parameters2).
The Bioinformatics Service Platform (BSP) has its own domain and website at http://bsp.ac.za/. We also host Globus endpoints at chpcbio#bio.chpc.ac.za and chpcbio#globus.chpc.ac.za.
Web Portal Access
Galaxy-access has been provided in the past and may be made available in the future. Additionally the JMS system will hopefully be integrated with the lengau cluster soon.
To transfer files inward using gridftp, the http://globus.org/ system can be used,
and is accessible via our endpoint named chpcbio#globus.chpc.ac.za. You should
use the same credentials used to log in via ssh.
Command Line Access
Before one gains access to the command line, you should have an account. In order to get an account you and your PI should both follow the instructions to apply for resources.
Once your registration has been approved then Linux and OSX users can simply open a terminal and connect via ssh to the server using a command of the form3):
localuser@my_linux:~ $ ssh username@lengau.chpc.ac.za Last login: Mon Feb 29 14:05:35 2016 from 10.128.23.235 username@login1:~ $
where user is the username you are assigned upon registration. Windows users can download the putty client 4).
Once connected users can: use the modules system to get access to bioinformatics programs; create job scripts using editors such as vim5) or nano6); and finally submit and monitor their jobs.
Using Modules
For now a quick and simple way of getting access to the bioinformatics software is using the module function. Running:
username@login2:~ $ module avail
will present you with the various modules available on the system and you should see something like:
------------------------------------------------ /cm/local/modulefiles ------------------------------------------------ cluster-tools/7.1 freeipmi/1.4.8 mvapich2/mlnx/gcc/64/2.1 use.own cluster-tools-dell/7.1 gcc/5.1.0 null version cmd ipmitool/1.8.15 openldap cmsh module-git openmpi/mlnx/gcc/64/1.8.8 dot module-info shared ----------------------------------------------- /cm/shared/modulefiles ------------------------------------------------ acml/gcc/64/5.3.1 chpc/python/anaconda/2 acml/gcc/fma4/5.3.1 chpc/python/anaconda/3 acml/gcc/mp/64/5.3.1 chpc/qespresso/5.3.0/openmpi-1.8.8/gcc-5.1.0 acml/gcc/mp/fma4/5.3.1 chpc/R/3.2.3-gcc5.1.0 acml/gcc-int64/64/5.3.1 chpc/vasp/5.3/openmpi-1.8.8/gcc-5.1.0 acml/gcc-int64/fma4/5.3.1 chpc/zlib/1.2.8/intel/16.0.1 acml/gcc-int64/mp/64/5.3.1 cmgui/7.1 acml/gcc-int64/mp/fma4/5.3.1 default-environment acml/open64/64/5.3.1 gdb/7.9 acml/open64/fma4/5.3.1 hdf5/1.6.10 acml/open64/mp/64/5.3.1 hdf5_18/1.8.14 acml/open64/mp/fma4/5.3.1 hpl/2.1 acml/open64-int64/64/5.3.1 hwloc/1.9.1 acml/open64-int64/fma4/5.3.1 intel/compiler/64/15.0/2015.5.223 acml/open64-int64/mp/64/5.3.1 intel-cluster-checker/2.2.2 acml/open64-int64/mp/fma4/5.3.1 intel-cluster-runtime/ia32/3.7 blas/gcc/64/3.5.0 intel-cluster-runtime/intel64/3.7 blas/open64/64/3.5.0 intel-cluster-runtime/mic/3.7 bonnie++/1.97.1 intel-tbb-oss/ia32/43_20150424oss chpc/amber/12/openmpi-1.8.8/gcc-5.1.0 intel-tbb-oss/intel64/43_20150424oss chpc/amber/14/openmpi-1.8.8/gcc-5.1.0 iozone/3_430 chpc/BIOMODULES iperf/3.0.11 chpc/cp2k/2.6.2/openmpi-1.8.8/gcc-5.1.0 lapack/gcc/64/3.5.0 chpc/dlpoly/1.9/openmpi-1.8.8/gcc-5.1.0 lapack/open64/64/3.5.0 chpc/dlpoly/4.07/openmpi-1.8.8/gcc-5.1.0 mpich/ge/gcc/64/3.1.4 chpc/dlpoly/4.08/openmpi-1.8.8/gcc-5.1.0 mpich/ge/open64/64/3.1.4 chpc/gaussian09/D01 mpiexec/0.84_432 chpc/gaussian09/E01 mvapich/gcc/64/1.2rc1 chpc/gromacs/5.1.2/openmpi-1.8.8/gcc-5.1.0 mvapich/open64/64/1.2rc1 chpc/hdf5/1.8.16/intel/16.0.1 netcdf/gcc/64/4.3.3.1 chpc/lammps/16Feb16/openmpi-1.8.8/gcc-5.1.0 netcdf/open64/64/4.3.3.1 chpc/namd/2.11/openmpi-1.8.8/gcc-5.1.0 netperf/2.6.0 chpc/netcdf/4.4.0-C/intel/16.0.1 open64/4.5.2.1 chpc/netcdf/4.4.3-F/intel/16.0.1 openblas/dynamic/0.2.14 chpc/openmpi/1.10.2/gcc-5.1.0 openlava/3.0 chpc/openmpi/1.10.2/intel-16.0.1 openmpi/pgi/64/1.8.5 chpc/openmpi/1.8.8/gcc-5.1.0 puppet/3.7.5 chpc/openmpi/1.8.8/intel-16.0.1 scalapack/gcc/64/1.8.0 chpc/parallel_studio_xe/16.0.1/2016.1.150 scalapack/open64/64/1.8.0 chpc/parallel_studio_xe/64/16.0.1/2016.1.150 sge/2011.11p1 chpc/python/2.7.11 slurm/14.11.6 chpc/python/3.5.1 torque/5.1.0
Bioinformatics modules are expected to add a lot to that list and so have a list of their own. Running
username@login2:~ $ module add chpc/BIOMODULES
followed by
username@login2:~ $ module avail
will result in the following being added to the above list (this should be much expanded as various applications are added to the system):
----------------------------------------- /apps/chpc/scripts/modules/bio/app ------------------------------------------ anaconda/2 doxygen/1.8.11 java/1.8.0_73 ncbi-blast/2.3.0/intel R/3.2.3-gcc5.1.0 anaconda/3 git/2.8.1 mpiblast/1.6.0 python/2.7.11 texlive/2015 cmake/3.5.1 htop/2.0.1 ncbi-blast/2.3.0/gcc python/3.5.1
Now to make use of, blast say, one can type:
username@login2:~ $ module add ncbi-blast/2.3.0/gcc
The appropriate environmental variables are set (usually as simple as adding a directory to the search path). Running:
username@login2:~ $ module list
will show which modules have been loaded. Whereas:
username@login2:~ $ module del modulename
will unload a module. And finally:
username@login2:~ $ module show modulename
will show what module modulename actually does.
Create Job Scripts
Next one must create a job script such as the one below:
- my_job.qsub
#!/bin/bash #PBS -l select=1:ncpus=2 #PBS -l walltime=10:00:00 #PBS -q serial #PBS -P SHORTNAME #PBS -o /mnt/lustre/users/username/my_data/stdout.txt #PBS -e /mnt/lustre/users/username/my_data/stderr.txt #PBS -N TophatEcoli #PBS -M myemailaddress@someplace.com #PBS -m b module add chpc/BIOMODULES module add tophat/2.1.1 NP=`cat ${PBS_NODEFILE} | wc -l` EXE="tophat" ARGS="--num-threads ${NP} someindex reads1 reads2 -o output_dir" cd /mnt/lustre/users/username/my_data ${EXE} ${ARGS}
Note that username should be your username and SHORTNAME should be your research programme's code. More details on the job script file can be found in our PBS quickstart guide.
Submit Job Script
Finally submit your job using:
username@login2:~ $ qsub my_job.qsub 192757.sched01 username@login2:~ $
where 192757.sched01 is the jobID that is returned.
Monitor jobs
Jobs can then be monitored/controlled in several ways:
qstat
check status of pending and running jobs
username@login2:~ $ qstat -u username sched01: Req'd Req'd Elap Job ID Username Queue Jobname SessID NDS TSK Memory Time S Time --------------- -------- -------- ---------- ------ --- --- ------ ----- - ----- 192759.sched01 username serial TophatEcol -- 1 24 -- 00:02 Q -- username@login2:~ $
check status of particular job
username@login2:~ $ qstat -f 192759.sched01 Job Id: 192759.sched01 Job_Name = TophatEcoli Job_Owner = username@login2.cm.cluster resources_used.cpupercent = 0 resources_used.cput = 00:00:00 resources_used.mem = 0kb resources_used.ncpus = 96 resources_used.vmem = 0kb resources_used.walltime = 00:00:00 job_state = R queue = serial server = sched01 Checkpoint = u ctime = Mon Oct 10 06:57:13 2016 Error_Path = login2.cm.cluster:/mnt/lustre/users/username/my_data/stderr.txt exec_host = cnode0962/0*24 exec_vnode = (cnode0962:ncpus=24) Hold_Types = n Join_Path = n Keep_Files = n Mail_Points = a mtime = Mon Oct 10 06:57:15 2016 Output_Path = login2.cm.cluster:/mnt/lustre/users/username/my_data/stdout.txt Priority = 0 qtime = Mon Oct 10 06:57:13 2016 Rerunable = True Resource_List.ncpus = 24 Resource_List.nodect = 1 Resource_List.place = free Resource_List.select = 1:ncpus=24 Resource_List.walltime = 00:02:00 stime = Mon Oct 10 06:57:15 2016 session_id = 36609 jobdir = /mnt/lustre/users/username substate = 42 Variable_List = PBS_O_SYSTEM=Linux,PBS_O_SHELL=/bin/bash, PBS_O_HOME=/home/dane,PBS_O_LOGNAME=username,PBS_O_WORKDIR=/mnt/lustre/users/username/my_data, PBS_O_LANG=en_ZA.UTF-8, PBS_O_PATH=/apps/chpc/bio/anaconda3/bin:/apps/chpc/bio/R/3.3.1/gcc-6.2 .0/bin:/apps/chpc/bio/bzip2/1.0.6/bin:/apps/chpc/bio/curl/7.50.0/bin:/a pps/chpc/bio/lib/png/1.6.21/bin:/apps/chpc/bio/openmpi/2.0.0/gcc-6.2.0_ java-1.8.0_73/bin:... comment = Job run at Mon Oct 10 at 06:57 on (cnode0962:ncpus=24)+(cnode0966 :ncpus=24)+(cnode0971:ncpus=24)+(cnode0983:ncpus=24) etime = Mon Oct 10 06:57:13 2016 umask = 22 run_count = 1 eligible_time = 00:00:00 Submit_arguments = my_job.qsub pset = rack=cx14 project = SHORTNAME username@login01:~ $
canceljob
username@login01:~ $ qdel 192759.sched01 username@login01:~ $
Basic examples
Blast
Running Blast using gnu parallel
Several examples of running blast can be found in this page of using fault tolerant blast.
Running Blast on sun cluster
Big thanks to Peter van Heusden for developing this script.
- sun_blast.sh
#!/bin/bash WORKDIR="/export/home/${USER}/scratch5/blast_proj" INPUT_FASTA=${WORKDIR}/data_set.fa.gz BLAST_E_VAL="1e-3" BLAST_DB="/lustre/SCRATCH5/groups/bioinfo/DBs/BLAST/nr" JOBTYPE=nehalem THREADS=8 BLAST_HOURS=0 BLAST_MINUTES=30 ID_FMT="%01d" SPLIT_PREFIX="sub_set" MAIL_ADDRESS="youremail@somewhere.ac.za" zcat ${INPUT_FASTA} | csplit -z -f ${WORKDIR}/${SPLIT_PREFIX} -b "${ID_FMT}.split.fasta" - '/^>/' '{*}' NUM_PARTS=$(ls sub_set*.split.fasta | wc -l) START=0 END=$(expr $NUM_PARTS - 1) TMPSCRIPT=thejob.sh # note: make a distinction between variables set by the containing script (e.g. WORKDIR) and # ones set in the script (e.g. INDEX). The ones set in the script need to be escaped out cat >${TMPSCRIPT} << END #!/bin/bash #PBS -l select=1:ncpus=${THREADS}:jobtype=${JOBTYPE} #PBS -l place=excl:group=nodetype #PBS -l walltime=${BLAST_HOURS}:${BLAST_MINUTES}:00 #PBS -q workq #PBS -m ae #PBS -M ${MAIL_ADDRESS} . /etc/profile.d/modules.sh module add blast/2.2.29+ INDEX="${WORKDIR}/${SPLIT_PREFIX}\${PBS_ARRAY_INDEX}" INFILE="\${INDEX}.split.fasta" OUTFILE="\${INDEX}.blastx.xml" cd ${WORKDIR} blastx -num_threads 8 -evalue ${BLAST_E_VAL} -db ${BLAST_DB} -outfmt 5 -query \${INFILE} -out \${OUTFILE} END BLAST_JOBID=$(qsub -N sunblast -J ${START}-${END} ${TMPSCRIPT} | cut -d. -f1) echo "submitted: ${BLAST_JOBID}" rm ${TMPSCRIPT} cat >${TMPSCRIPT} << END #!/bin/bash #PBS -l select=1:ncpus=1:jobtype=${JOBTYPE} #PBS -l place=free:group=nodetype #PBS -l walltime=1:00:00 #PBS -q workq #PBS -m ae #PBS -M ${MAIL_ADDRESS} #PBS -W depend=afterok:${BLAST_JOBID} cd ${WORKDIR} tar jcf blast-xml-output.tar.bz2 *.blastx.xml END qsub -N tarblast ${TMPSCRIPT} rm ${TMPSCRIPT}
This script is designed to be run from the login node – it creates the job job scripts themselves and submits them. There are a number of things to notice:
- The use of heredocs. These allow us to embed scripts that are to be run into another script. Here we can see that they output the text between “cat >${TMPSCRIPT} « END” and “END” into the file ${TMPSCRIPT}
- The use of job-arrays – these allow us to submit multiple independent jobs as sub-jobs of one larger script. The line “BLAST_JOBID=$(qsub -N sunblast -J ${START}-${END} ${TMPSCRIPT} | cut -d. -f1)” does multiple things:
- It submits a job-array with the -J option which contains a STARTing number and an ENDing number. The END value in turn is informed by the line “NUM_PARTS=$(ls sub_set*.split.fasta | wc -l)” which counts the number of sub-fasta files which were created using the “csplit”7) command.
- the “cut -d. -f1” is used to grab the job identifier that is returned from the scheduler when the job is submitted. This is assigned to the variable BLAST_JOBID.
- Note that job-arrays create the environmental variable PBS_ARRAY_INDEX which is used as a parameter for both the blast's input file and the blast's output file parameters.
- Another important aspect of the job array is that the walltime parameter is the longest time you'd expect the sub-jobs to run in. So in this case we've divided a fasta file into many smaller faster files – one for each sequence. In the event that your original sequences have widely differing lengths it may pay to have a different approach to the division – perhaps one that results in the sub-fastas having similar sizes.
- The use of job dependencies. We see it in the second heredoc in the line “#PBS -W depend=afterok:${BLAST_JOBID}”. What this line does is that it says the job script only runs after the job with ID ${BLAST_JOBID} has successfully finished running, i.e. this job will not run if there are problems with the first job.
Blast2Go
A local instance of blast2go is available at the CHPC. It is accessible from outside the CHPC, however it does require you to set up some port forwarding.
Port Forwarding
This is accomplished via setting up port forwarding in your SSH session. In windows this is usually done in PuTTY, and in unix/osx this is done on the command line. Note: This connection must stay on for as long as you wish to use CHPC's blast2go database.
PuTTY
When setting up the ssh connection you should go to: connection → SSH → Tunnels. Then add 3306 for Source port and 10.128.15.90:3306 for Destination. Then click Add.
You should then save your session (so that you don't have to fill this information in every time) and connect (using your normal CHPC login details).
SSH
Your normal ssh command will change to look more like this:
localuser@my_linux:~ $ ssh username@sun.chpc.ac.za -L 3306:10.128.15.90:3306 Last login: Tue Jan 28 14:05:35 2014 from 10.128.23.235 username@login01:~ $
blast2go Configuration
First you should go to the blast2go website and start blast2go as normal by clicking on the please click here link8).
A small file will download and you should then run it, and then blast2go proceeds to download the rest of the application.
Once blast2go is running go to: Tools → General Settings → DataAccess Settings.
Then set:
- Own Database
- DB Name: b2gdbFeb2014
- DB Host: localhost
- DB User: b2guser
- DB Password: blast4it
and click OK.
Then you will see in the bottom window/tab that it has connected to the database 9), and should also confirmed right at the bottom in the status message10).
Finally you may test the everything is working as expected by clicking on the white arrow in the green circle and confirm that you get the GO graph.
Gromacs
If you would like to try running gromacs on the gpu please take a look at this.
The job script that follows is for running an MPI compiled version of gromacs 4.6.1 on nehalem. There are many different versions of gromacs, to see what's available try:
user@login01:~ $ module avail
The following example is for working with one of the “_nehalem” gromacs modules – note it's quite important to use the correct version as the input data changes with versions…
Job script
- gromacs_nehalem.qsub
#!/bin/bash #PBS -l select=10:ncpus=8:mpiprocs=8:jobtype=nehalem,place=excl #PBS -l walltime=00:40:00 #PBS -q workq #PBS -M user@someinstitution.ac.za #PBS -m be #PBS -V #PBS -e /lustre/SCRATCH5/users/USERNAME/gromacs_data/std_err.txt #PBS -o /lustre/SCRATCH5/users/USERNAME/gromacs_data/std_out.txt #PBS -N GROMACS_JOB #PBS -mb MODULEPATH=/opt/gridware/bioinformatics/modules:$MODULEPATH source /etc/profile.d/modules.sh #######module add module add gromacs/4.6.1_nehalem OMP_NUM_THREADS=1 NP=`cat ${PBS_NODEFILE} | wc -l` EXE="mdrun_mpi" ARGS="-s XXX -deffnm YYYY" cd /lustre/SCRATCH5/users/USERNAME/gromacs_data mpirun -np ${NP} -machinefile ${PBS_NODEFILE} ${EXE} ${ARGS}
Submit your job
Finally submit your job using:
user@login01:~ $ qsub gromacs_nehalem.qsub
bowtie
Things to note about this script – bowtie currently does not run across multiple nodes. So using anything other than select=1 will result in compute resources being wasted11).
Job script
Then your job script called gromacs_nehalem.qsub will look something like this:
- bowtie_script.qsub
#! /bin/bash #PBS -l select=1:ncpus=12 #PBS -l place=excl #PBS -l walltime=06:00:00 #PBS -q workq #PBS -o /export/home/username/scratch5/some_reads/stdout.txt #PBS -e /export/home/username/scratch5/some_reads/stderr.txt #PBS -M youremail@address.com #PBS -m be #PBS -N bowtiejob ################## MODULEPATH=/opt/gridware/bioinformatics/modules:$MODULEPATH source /etc/profile.d/modules.sh #######module add module add bowtie2/2.2.2 NP=`cat ${PBS_NODEFILE} | wc -l` EXE="bowtie2" forward_reads="A_reads1.fq,B_reads_1.fq" reverse_reads="A_reads1.fq,B_reads_1.fq" output_file="piggy_hits.sam" ARGS="sscrofa --shmem --threads ${NP} --sam -q -1 ${forward_reads} -2 ${reverse_reads} ${output_file}" ${EXE} ${ARGS}
Note: username should contain your actual user name!
Submit your job
Finally submit your job using:
user@login01:~ $ qsub bowtie_script.qsub
NAMD2
If you would like to try running namd2 on the GPU please take a look at this.
The job script that follows is for running a NAMD over the infiniband. Note that this does not use MPI so the script is somewhat different from other scripts you may see here.
Job script
- namd.qsub
#!/bin/bash #PBS -l select=10:ncpus=12:mpiprocs=12 #PBS -l place=excl #PBS -l walltime=00:05:00 #PBS -q workq #PBS -o /export/home/username/scratch5/namd2/stdout.txt #PBS -e /export/home/username/scratch5/namd2/stderr.txt #PBS -m ae #PBS -M youremail@address.com #PBS -N NAMD_bench . /etc/profile.d/modules.sh MODULEPATH=/opt/gridware/bioinformatics/modules:${MODULEPATH} module add NAMD/2.10_ibverbs cd /export/home/${USER}/scratch5/namd2 pbspro_namd apoa1.namd
Submit your job
Finally submit your job using:
user@login01:~ $ qsub namd.qsub
bowtie
Things to note about this script – bowtie currently does not run across multiple nodes. So using anything other than select=1 will result in compute resources being wasted12).
Job script
Then your job script called gromacs_nehalem.qsub will look something like this:
- bowtie_script.qsub
#! /bin/bash #PBS -l select=1:ncpus=12 #PBS -l place=excl #PBS -l walltime=06:00:00 #PBS -q workq #PBS -o /lustre/SCRATCH5/users/username/some_reads/stdout.txt #PBS -e /lustre/SCRATCH5/users/username/some_reads/stderr.txt #PBS -M youremail@address.com #PBS -m be #PBS -N bowtiejob ################## MODULEPATH=/opt/gridware/bioinformatics/modules:$MODULEPATH source /etc/profile.d/modules.sh #######module add module add bowtie2/2.2.2 NP=`cat ${PBS_NODEFILE} | wc -l` EXE="bowtie2" forward_reads="A_reads1.fq,B_reads_1.fq" reverse_reads="A_reads1.fq,B_reads_1.fq" output_file="piggy_hits.sam" ARGS="sscrofa --shmem --threads ${NP} --sam -q -1 ${forward_reads} -2 ${reverse_reads} ${output_file}" cd /lustre/SCRATCH5/users/username/some_reads ${EXE} ${ARGS}
Note: username should contain your actual user name!
Submit your job
Finally submit your job using:
user@login01:~ $ qsub bowtie_script.qsub
R/bioconductor
There is an example here on how one might use R at the chp
tophat
cufflinks
tuxedo
biopython
velvet
SOAP
Advanced examples
Databases
Databases are accessible on the cluster in the
/lustre/SCRATCH5/groups/bioinfo/DBs
directory. Alternatively they are also mirrored on the bio machine.
Support
Please contact us to: request software updates/installs; download big datasets; get advice on the best way to run your analysis; or to tell us what is/isn't working!
1)
Because they might just give you some addiotional hints
2)
especially the -P parameter
3)
Note that localuser@my_linux:~ $ is not part of the command
4)
Here is the getting started with putty guide
7)
csplit is a very useful tool – google it!
8)
You may want to change the memory specifications here if you have lots of sequences
9)
Open database connection to database 'b2gdbFeb2014' on 'localhost' as 'b2guser', with…
10)
Connected to own database: localhost: b2gdbFeb2014
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