easy_qsub

Easily submitting multiple PBS jobs or running local jobs in parallel. Multiple input files supported.

Submitting PBS jobs

easy_qsub submits PBS jobs with script template, avoid repeatedly editing PBS scripts.

Default template (~/.easy_qsub/default.pbs):

#PBS -S /bin/bash
#PBS -N $name
#PBS -q $queue
#PBS -l ncpus=$ncpus
#PBS -l mem=$mem
#PBS -l walltime=$walltime
#PBS -V

cd $$PBS_O_WORKDIR
echo run on node: $$HOSTNAME >&2

$cmd

Generated PBS scripts are saved in /tmp/easy_qsub-user. If jobs are submitted successfuly, PBS scripts will be moved to current directory. If not, they will be removed.

Support for multiple inputs

Inspired by qtask, multiple inputs is supported (See example 2). If "{}" appears in a command, it will be replaced with the current filename. Four formats are supported. For example, for a file named "/path/reads.fq.gz":

format	target	result
{}	full path	/path/reads.fq.gz
{%}	basename	reads.fq.gz
{^.fq.gz}	remove suffix from full path	/path/reads
{%^.fq.gz}	remove suffix from basename	reads

Running local jobs in parallel

It also support runing commands locally with option -lp (parallelly) or -ls (serially). This make it easy to switch between cluster and local machine.

Best partner: cluster_files

To make best use of the support for multiple input, a script cluster_files is added to cluster files into multiple directories by creating symbolic links or moving files (See example 3,4). It's useful for programs which take one directory as input.

Another useful scene is to apply different jobs to a same dataset. One bad directory structure is:

datasets/
├── A
├── A.stage1
├── A.stage2
├── B
├── B.stage1
└── B.stage2

A flexible structure can be organsize by cluster_files. Instead of changing original directory structure, using links could be more clear and flexible.

datasets
├── A
└── B
datasets.stage1
├── A
└── B
datasets.stage2
├── A
└── B

Examples

1. Submit a single job

   easy_qsub 'ls -lh'

2. Submit multiple jobs, runing fastqc for a lot of fq.gz files

   easy_qsub -n 8 -m 2GB 'mkdir -p QC/{%^.fq.gz}.fastqc; zcat {} | fastqc -o QC/{%^.fq.gz}.fastqc stdin' *.fq.gz

Excuted commands are:

mkdir -p QC/read_1.fastqc; zcat read_1.fq.gz | fastqc -o QC/read_1.fastqc stdin
mkdir -p QC/read_2.fastqc; zcat read_2.fq.gz | fastqc -o QC/read_2.fastqc stdin

Dry run with -vv

easy_qsub -n 8 -m 2GB 'mkdir -p QC/{%^.fq.gz}.fastqc; zcat {} | fastqc -o QC/{%^.fq.gz}.fastqc stdin' *.fq.gz -vv

3. Supposing a directory rawdata containing paired files as below.

   $ tree rawdata rawdata ├── A2_1.fq.gz ├── A2_1.unpaired.fq.gz ├── A2_2.fq.gz ├── A2_2.unpaired.fq.gz ├── A3_1.fq.gz ├── A3_1.unpaired.fq.gz ├── A3_2.fq.gz ├── A3_2.unpaired.fq.gz └── README.md

And I have a program script.py, which takes a directory as input and do some thing with the paired files. Command is like this, script.py dirA.

It is slow by submiting jobs like example 2), handing A2_*.fq.gz and then A3_*.fq.gz. We can split rawdata directory into multiple directories (cluster files by the prefix), and submit jobs for all directories.

cluster_files -p '(.+?)_\d\.fq\.gz$' rawdata -o rawdata.cluster

tree rawdata.cluster/
rawdata.cluster/
├── A2
│   ├── A2_1.fq.gz -> ../../rawdata/A2_1.fq.gz
│   └── A2_2.fq.gz -> ../../rawdata/A2_2.fq.gz
└── A3
    ├── A3_1.fq.gz -> ../../rawdata/A3_1.fq.gz
    └── A3_2.fq.gz -> ../../rawdata/A3_2.fq.gz

easy_qsub 'script.py {}' rawdata.split/*

Another example (e.g. some assembler can handle unpaired reads too):

cluster_files -p '(.+?)_\d.*\.fq\.gz$' rawdata -o rawdata.cluster2

tree rawdata.cluster2
rawdata.cluster2
├── A2
│   ├── A2_1.fq.gz -> ../../rawdata/A2_1.fq.gz
│   ├── A2_1.unpaired.fq.gz -> ../../rawdata/A2_1.unpaired.fq.gz
│   ├── A2_2.fq.gz -> ../../rawdata/A2_2.fq.gz
│   └── A2_2.unpaired.fq.gz -> ../../rawdata/A2_2.unpaired.fq.gz
└── A3
    ├── A3_1.fq.gz -> ../../rawdata/A3_1.fq.gz
    ├── A3_1.unpaired.fq.gz -> ../../rawdata/A3_1.unpaired.fq.gz
    ├── A3_2.fq.gz -> ../../rawdata/A3_2.fq.gz
    └── A3_2.unpaired.fq.gz -> ../../rawdata/A3_2.unpaired.fq.gz

4. Another example (complexed directory structure)

   tree rawdata2 rawdata2 ├── OtherDir │ └── abc.fq.gz.txt ├── S1 │ ├── A2_1.fq.gz │ ├── A2_1.unpaired.fq.gz │ ├── A2_2.fq.gz │ ├── A2_2.unpaired.fq.gz │ ├── A4_1.fq.gz │ └── A4_2.fq.gz └── S2 ├── A3_1.fq.gz ├── A3_1.unpaired.fq.gz ├── A3_2.fq.gz └── A3_2.unpaired.fq.gz

   cluster_files -p '(.+?)_\d.fq.gz$' rawdata2/

   tree rawdata2.cluster/ rawdata2.cluster/ ├── A2 │ ├── A2_1.fq.gz -> ../../rawdata2/S1/A2_1.fq.gz │ └── A2_2.fq.gz -> ../../rawdata2/S1/A2_2.fq.gz ├── A3 │ ├── A3_1.fq.gz -> ../../rawdata2/S2/A3_1.fq.gz │ └── A3_2.fq.gz -> ../../rawdata2/S2/A3_2.fq.gz └── A4 ├── A4_1.fq.gz -> ../../rawdata2/S1/A4_1.fq.gz └── A4_2.fq.gz -> ../../rawdata2/S1/A4_2.fq.gz

   cluster_files -p '(.+?)_\d.fq.gz$' rawdata2/ -k -f # keep original dir structure

   tree rawdata2.cluster/ rawdata2.cluster/ ├── S1 │ ├── A2 │ │ ├── A2_1.fq.gz -> ../../../rawdata2/S1/A2_1.fq.gz │ │ └── A2_2.fq.gz -> ../../../rawdata2/S1/A2_2.fq.gz │ └── A4 │ ├── A4_1.fq.gz -> ../../../rawdata2/S1/A4_1.fq.gz │ └── A4_2.fq.gz -> ../../../rawdata2/S1/A4_2.fq.gz └── S2 └── A3 ├── A3_1.fq.gz -> ../../../rawdata2/S2/A3_1.fq.gz └── A3_2.fq.gz -> ../../../rawdata2/S2/A3_2.fq.gz

Installation

easy_qsub and cluster_files is a single script written in Python using standard library. It's Python 2/3 compatible, version 2.7 or later.

You can simply save the script easy_qsub and cluster_files to directory included in environment PATH, e.g /usr/local/bin.

Or

git clone https://github.com/shenwei356/easy_qsub.git
cd easy_qsub
sudo copy easy_qsub cluster_files /usr/local/bin

Usage

easy_qsub

usage: easy_qsub [-h] [-lp | -ls] [-N NAME] [-n NCPUS] [-m MEM] [-q QUEUE]
                 [-w WALLTIME] [-t TEMPLATE] [-o OUTFILE] [-v]
                 command [files [files ...]]

Easily submitting PBS jobs with script template. Multiple input files
supported.

positional arguments:
  command               command to submit
  files                 input files

optional arguments:
  -h, --help            show this help message and exit
  -lp, --local_p        run commands locally, parallelly
  -ls, --local_s        run commands locally, serially
  -N NAME, --name NAME  job name
  -n NCPUS, --ncpus NCPUS
                        cpu number [logical cpu number]
  -m MEM, --mem MEM     memory [5gb]
  -q QUEUE, --queue QUEUE
                        queue [batch]
  -w WALLTIME, --walltime WALLTIME
                        walltime [30:00:00:00]
  -t TEMPLATE, --template TEMPLATE
                        script template
  -o OUTFILE, --outfile OUTFILE
                        output script
  -v, --verbose         verbosely print information. -vv for just printing
                        command not creating scripts and submitting jobs

Note: if "{}" appears in a command, it will be replaced with the current
filename. More format supported: "{%}" for basename, "{^suffix}" for clipping
"suffix", "{%^suffix}" for clipping suffix from basename. See more:
https://github.com/shenwei356/easy_qsub

cluster_files

usage: cluster_files [-h] [-o OUTDIR] [-p PATTERN] [-k] [-m] [-f] indir

clustering files by regular expression [V3.0]

positional arguments:
  indir                 source directory

optional arguments:
  -h, --help            show this help message and exit
  -o OUTDIR, --outdir OUTDIR
                        out directory [<indir>.cluster]
  -p PATTERN, --pattern PATTERN
                        pattern (regular expression) of files in indir. if not
                        given, it will be the longest common substring of the
                        files. GROUP (parenthese) should be in the regular
                        expression. Captured group will be the cluster name.
                        e.g. "(.+?)_\d\.fq\.gz"
  -k, --keep            keep original dir structure
  -m, --mv              moving files instead of creating symbolic links
  -f, --force           force file overwriting, i.e. deleting existed out
                        directory

Copyright

Copyright (c) 2015-2017, Wei Shen (shenwei356@gmail.com)

MIT License