Python implementation of Java SNP calling pipeline (https://github.com/DSGlab/SNPCallingPipeline/)
Project description
ABOUT
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Python implementation of Java SNP calling pipeline (https://github.com/DSGlab/SNPCallingPipeline).
Usage is descriped below. For consistency the configuration file is exactly as described in the Java code.
Descriptions of the various options in the Java code is given at https://github.com/DSGlab/SNPCallingPipeline.
An example configuration file is included in this directory.
USAGE
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
usage: pySNPCallingPipeline.py [-h] -c CONF_FILE [--aln_only] [--no_aln]
[--local] [--submit] [--subset SUBSET]
[--def_run]
Run pySNPCallingPipeline
optional arguments:
-h, --help show this help message and exit
-c CONF_FILE, --conf CONF_FILE
A configuration file is required to run
pySNPCallingPipeline.
--aln_only Alignment only, default is FALSE.
--no_aln Run all analysis using pre-run alignments, default is
FALSE.
--local Is this a LOCAL run or should SLURM files be created?
Default is True.
--submit If running a supercomputing cluster, should only slurm
files be created or should the jobs be submitted as
well.
--subset SUBSET Provide a comma seperated list of a subset of
"alignment, getHQSNPs, intraClonalSNPs, checkSNPs,
filterSNPs"
--def_run Default: run entire calculation locally.
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Python implementation of Java SNP calling pipeline (https://github.com/DSGlab/SNPCallingPipeline).
Usage is descriped below. For consistency the configuration file is exactly as described in the Java code.
Descriptions of the various options in the Java code is given at https://github.com/DSGlab/SNPCallingPipeline.
An example configuration file is included in this directory.
USAGE
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
usage: pySNPCallingPipeline.py [-h] -c CONF_FILE [--aln_only] [--no_aln]
[--local] [--submit] [--subset SUBSET]
[--def_run]
Run pySNPCallingPipeline
optional arguments:
-h, --help show this help message and exit
-c CONF_FILE, --conf CONF_FILE
A configuration file is required to run
pySNPCallingPipeline.
--aln_only Alignment only, default is FALSE.
--no_aln Run all analysis using pre-run alignments, default is
FALSE.
--local Is this a LOCAL run or should SLURM files be created?
Default is True.
--submit If running a supercomputing cluster, should only slurm
files be created or should the jobs be submitted as
well.
--subset SUBSET Provide a comma seperated list of a subset of
"alignment, getHQSNPs, intraClonalSNPs, checkSNPs,
filterSNPs"
--def_run Default: run entire calculation locally.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pySNPCall-0.1.tar.gz
(13.6 kB
view details)
Built Distribution
pySNPCall-0.1-py3-none-any.whl
(20.9 kB
view details)
File details
Details for the file pySNPCall-0.1.tar.gz
.
File metadata
- Download URL: pySNPCall-0.1.tar.gz
- Upload date:
- Size: 13.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.5.0 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8492614380d4b857c5d28018f6d852a012775e8e7d6d6aeff834977283a08f18 |
|
MD5 | 7d0ddc24491ea4719c0cf1ca534e5d7e |
|
BLAKE2b-256 | 72ec1d1c4d78c512201879886574ba94ce3adab2e8a430f31562e644892ce14f |
File details
Details for the file pySNPCall-0.1-py3-none-any.whl
.
File metadata
- Download URL: pySNPCall-0.1-py3-none-any.whl
- Upload date:
- Size: 20.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.5.0 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a2cfc7fb2ebe30f5ccbf1d64bf905e6d967cb04a11c403ebcb0e8dd0b123a2fd |
|
MD5 | f4e37298713c385784132822e80e34a3 |
|
BLAKE2b-256 | 5faf0be239332c753caba8e9e5af16c96534c51d76095ec96117b9a9ce61421b |