Utility to create and distribute jobs on a queue system. It is particularly suited to process BigData (i.e. NGS analyses), helping generating hundreds of different jobs with ease to crunch large datasets.
This utility is a command line based tool built around the concept of a template that can be reused to generate tens, hundreds or thousands of different jobs to be sent on a queue system.
The tool for now supports only PBS queue systems, but can be easily expanded to account also for other queueing systems.
A typical example
Let's say I have a bunch of FastQ files that I want to analyze using my favorite reads mapping tool. These files come from a typical Illumina paired end sequencing and I have 60 files from the read 1 and another 60 files from the read 2. Given that I have a distributed system I want to spread the alignments on the cluster (or grid), to speed up the analysis as much as possible.
Instead of having to manually create a number of running scripts or rewrite for every analysis a new script to do this work, BioGrid can help you saving time handling all of this.
bio-grid -i "/data/Project_X/Sample_Y/*_R1_*.fastq.gz","/data/Project_X/Sample_Y/*_R2_*.fastq.gz" -n bowtie_mapping -c "/software/bowtie2 -x /genomes/genome_index -p 8 -1 <input1> -2 <input2> > <output>.sam" -o /data/Project_X/Sample_Y_mapping -s 1 -p 8
What is happening here is the following:
-ioptions specifies the input files or, as in this case, the location where to find input files based on a typical wildcard expression. You can actually specify as many input files/locations as you need using a comma separated list.
-nspecify the job name
-cis the command line to be executed on the cluster / grid system. What BioGrid does is to fill in the
<output>placeholders with the corresponding parameters passed on the command line. This is done for each input file (or each group of input files) and BioGrid will check if the
<output>placeholder has an extension (like .sam, .out etc.) and will generate a unique output file name for each job.
-oset the location where output files for each job will be saved. Only provide the folder where you want to save the output file(s), BioGrid will take care of generating a unique file name for the output, if needed. Check the Output management for more details.
-sis a key parameter to specify the granularity of the jobs, setting the number of input files (or group of files, when more than one input placeholder is present in the command line) to be used for each job. So, going back to the FastQ example, if -s 1 is specified, each job will be run with exactly one FastQ R1 file and one FastQ R2 file. This gives you a great power in deciding how to split the entire dataset analysis across multiple computing nodes.
-pparameter indicates how many processes we want to use for each job. This number needs to match with the actual number of threads / processes that our command or tool will use for the analysis.
All of this is just turned into a submission script that will look like this:
#!/bin/bash #PBS -N bowtie_mapping #PBS -l ncpus=8 mkdir -p /data/Project_X/Sample_Y_mapping /software/bowtie2 -x /genomes/genome_index -p 8 -1 /data/Project_X/Sample_Y/Sample_Y_L001_R1_001.fastq.gz -2 Sample_Y_L001_R2_001.fastq.gz > /data/Project_X/Sample_Y_mapping/bowtie_mapping-output_001.sam
and this will be repeated for every input file, according to the -s parameter. So, in this case given that we have 2 input files for each command line and that we had 60 R1 and 60 R2 FastQ files and we have specified "-s 1", 60 different jobs will be created and submitted, each with a specific read pair to be processed by Bowtie.
For each job, BioGrid will set an output name according to a UUID generated on the fly and the combination of the job name plus an incremental number. So a typical output file name will look like this:
IMPORTANT: the UUID will be the same for all the jobs submitted in a same BioGrid run, the only changing part will be the incremental number.
If no extension is specified for the
<output> placeholder in the command line definition, BioGrid will assume the job will generate more than one output file and that those files will be saved into the folder specified by the "-o" option. Therefore it will manage the output as a whole directory, copying and/or removing the entire folder if
-e options are present (check the Other options section to see what these options are expected to do).
The same rule for output name apply also in the case of an output folder and the final directory will look like this:
without the incremental number, which is only used for output files.
If you want to do some Advanced stuff and run parameters testing, the output names will be changed accordingly by BioGrid. So if I am running BioGrid to test some parameter
-L for my favorite tool, and I am sampling it, with three different values, let's say 3, 7 and 10 the corresponding output files will be:
9ec55d90_tophat_001-param:3.sam 9ec55d90_tophat_001-param:7.sam 9ec55d90_tophat_001-param:10.sam
If you are using the
--param options to test non-numerical parameters, the corresponding parameter value (or name) will be appended to the output file name in the same way:
With BioGrid you can specify many different tasks for the job to execute, for example:
-tto execute only a single job, which is useful to test parameters
-rto specify a different location from the one used in
-o. This folder will be used to copy job outputs once terminated
-eto erease output files/folders specified by
-oonce a job is completed (useful in conjuction with
-rto delete local data on a computing node)
-dfor a dry run, to create submissions scripts without sending them in the queue system
The following BioGrid command line:
bio-grid -i "/data/Project_X/Sample_Y/*_R1_*.fastq.gz","/data/Project_X/Sample_Y/*_R2_*.fastq.gz" -n bowtie_mapping -c "/software/bowtie2 -x /genomes/genome_index -p 8 -1 <input1> -2 <input2> > <output>.sam" -o /data/Project_X/Sample_Y_mapping -s 1 -p 8 -r /results/Sample_Y_mapping -e
will be turned into this submission script:
#!/bin/bash #PBS -N bowtie_mapping #PBS -l ncpus=8 mkdir -p /data/Project_X/Sample_Y_mapping # output dir /software/bowtie2 -x /genomes/genome_index -p 8 -1 /data/Project_X/Sample_Y/Sample_Y_L001_R1_001.fastq.gz -2 Sample_Y_L001_R2_001.fastq.gz > /data/Project_X/Sample_Y_mapping/bowtie_mapping-output_001.sam # command line mkdir -p /results/Sample_Y_mapping # final location where to copy job output once terminated cp /data/Project_X/Sample_Y_mapping/bowtie_mapping-output_001.sam /results/Sample_Y_mapping # copy the outputs to the final location rm -f /data/Project_X/Sample_Y_mapping/bowtie_mapping-output_001.sam # deleting output data
For a complete list of current BioGrid parameters, type "bio-grid -h":
-n, --name NAME Analysis name -s, --split-number NUMBER Number of input files (or group of files) to use per job. If all the files in a location need to be used for a single job, just specify 'all' -p, --processes PROCESSES Number of processes per job -c, --command-line COMMANDLINE Command line to be executed -o, --output OUTPUT Output folder. Needs a <output> placeholder in the command line -r, --copy-to LOCATION Copy the output once a job is terminated -e, --erease-output Delete job output data when completed (useful to delete output temporary files on a computing node) -a, --params PARAM1,PARAM2... List of parameters to use for testing. Needs a <param> placeholder in the command line -d, --dry Dry run. Just write the job scripts without sending them in queue (for debugging or testing) -t, --test Start the mapping only with the first group of reads (e.g. for testing parameters) -i, --input INPUT1,INPUT2... Location where to find input files (accepts wildcards). Needs <input(1,2,3...> placeholder(s) in the command line --sep SEPARATOR Input file separator [Default: , ] --keep-scripts Keep all the running scripts created for all the jobs -h, --help Display this screen
Ok let's unleash the potential of BioGrid. By putting together an automatic system to generate and submit jobs on a queue systems and a command line template approach, we can do some interesting things.
Numerical parameters sampling and testing
The tipical scenario is when I have to run a tool on a new dataset and I would like to test different parameters to asses which are the better ones for my analysis. This can be easily done with BioGrid. For example:
bio-grid -i "/data/Project_X/Sample_Y/*_R1_*.fastq.gz","/data/Project_X/Sample_Y/*_R2_*.fastq.gz" -n bowtie_mapping -c "/software/bowtie2 -x /genomes/genome_index -p 8 -L <22,32,2> -1 <input1> -2 <input2> > <output>.sam" -o /data/Project_X/Sample_Y_mapping -s 1 -p 8 -r /results/Sample_Y_mapping -e -t
The key points here are the
-L <22,32,2> in the command line template and the
-t options of BioGrid. The first is a way to tell BioGrid to generate a number of similar jobs, each one with a different value for the parameter
-L. The values are decided based on the information passsed within the
- the first number is the first value that the parameter will take
- the second number is the last value that the parameter will take
- the third number is the increment to generate the range of values in between
So in this case, the
-L parameter will take 6 different values: 22, 24, 26, 28, 30 and 32.
Last but not least, the
-t option is essential so that only a single job per input file (or group of files) will be executed. Sampling parameters values is a typical combinatorial approach and this option avoids generating hundreds of different jobs only to sample a parameter. Coming back to the initial example, if I have 60 pairs of FastQ files, without the
-t option, the job number will be 60x6 = 360, which is just crazy when you only want to test different parameter values.
Others parameters sampling
If you want to sample non-numerical parameters, with BioGrid it is possible to use the
--params option. So for instance, if I want to run Bowtie on my dataset to assess the results differences using the
--fast options, I can do it easely in this way:
bio-grid -i "/data/Project_X/Sample_Y/*_R1_*.fastq.gz","/data/Project_X/Sample_Y/*_R2_*.fastq.gz" -n bowtie_mapping -c "/software/bowtie2 -x /genomes/genome_index -p 8 <param> -1 <input1> -2 <input2> > <output>.sam" -o /data/Project_X/Sample_Y_mapping -s 1 -p 8 -r /results/Sample_Y_mapping -e --param "--sensitive","--very-sensitive","--fast" -t
In this case, the key points are the
<param> placeholder in the command line and the corresponding
--params options in BioGrid, which specify a list of parameters to be used to generate and run different jobs, each one with a different parameter in the list. Again, even in this case, it is recommended to do parameters testing using the
-t option, which only runs a single job and not the full job array.
So far, BioGrid does not support, for each run, sampling more than one parameter at the same time.
Contributing to bioruby-grid
- Check out the latest master to make sure the feature hasn't been implemented or the bug hasn't been fixed yet.
- Check out the issue tracker to make sure someone already hasn't requested it and/or contributed it.
- Fork the project.
- Start a feature/bugfix branch.
- Commit and push until you are happy with your contribution.
- Make sure to add tests for it. This is important so I don't break it in a future version unintentionally.
- Please try not to mess with the Rakefile, version, or history. If you want to have your own version, or is otherwise necessary, that is fine, but please isolate to its own commit so I can cherry-pick around it.
Copyright (c) 2012 Francesco Strozzi. See LICENSE.txt for further details.