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https://github.com/AstraZeneca-NGS/VarDict
VarDict
https://github.com/AstraZeneca-NGS/VarDict
Last synced: about 2 months ago
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VarDict
- Host: GitHub
- URL: https://github.com/AstraZeneca-NGS/VarDict
- Owner: AstraZeneca-NGS
- License: mit
- Created: 2014-07-15T12:50:23.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2024-01-05T14:06:13.000Z (9 months ago)
- Last Synced: 2024-06-14T01:28:48.046Z (3 months ago)
- Language: Perl
- Size: 1.43 MB
- Stars: 186
- Watchers: 53
- Forks: 60
- Open Issues: 37
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
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- top-life-sciences - **AstraZeneca-NGS/VarDict** - 01-05 14:06:13 | (Ranked by starred repositories)
README
This is the Final Version of VarDict. No longer maintained.
VarDict
=======
VarDict is an ultra sensitive variant caller for both single and paired sample variant calling from BAM files.
VarDict implements several novel features such as amplicon bias aware variant calling from targeted
sequencing experiments, rescue of long indels by realigning bwa soft clipped reads and better scalability
than many Java based variant callers.
Due to the philosophy of VarDict in calling "everything", several downstream strategies have been developed
to filter variants to for example the most likely cancer driving events. These strategies are based on evidence
in different databases and/or quality metrics. http://bcb.io/2016/04/04/vardict-filtering/ provides an overview of
how to develop further filters for VarDict. The script at https://github.com/AstraZeneca-NGS/VarDict/blob/master/vcf2txt.pl
can be used to put the variants into a context by including information from dbSNP, Cosmic and ClinVar. We are open to
suggestions from the community on how to best narrow down to the variants of most interest.
A Java based drop-in replacement for vardict.pl is being developed at https://github.com/AstraZeneca-NGS/VarDictJava.
The Java implementation is approximately 10 times faster than the original
Perl implementation and does not depend
on samtools
To enable amplicon aware variant calling (single sample mode only; not supported in paired variant calling),
please make sure the bed file has 8 columns with the 7th and 8th columns containing the insert interval
(therefore subset of the 2nd and 3rd column interval). The bed files typically look similar to the below two
overlapping intervals:
``chr1 115247094 115247253 NRAS 0 . 115247117 115247232``
``chr1 115247202 115247341 NRAS 0 . 115247224 115247323``
For more information on amplicon aware calling please see https://github.com/AstraZeneca-NGS/VarDict/wiki/Amplicon-Mode-in-VarDict
VarDict is fully integrated in e.g. bcbio-nextgen, see https://github.com/chapmanb/bcbio-nextgen
Please cite VarDict:
Lai Z, Markovets A, Ahdesmaki M, Chapman B, Hofmann O, McEwen R, Johnson J, Dougherty B, Barrett JC, and Dry JR. VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research. Nucleic Acids Res. 2016, pii: gkw227.
The link to is article can be accessed through: http://nar.oxfordjournals.org/cgi/content/full/gkw227?ijkey=Tk8eKQcYwNlQRNU&keytype=ref
Coded by Zhongwu Lai 2014.
Requirements
------------
- Perl (uses /usr/bin/env perl)
- R (uses /usr/bin/env R)
- samtools (must be in path, not required if using the Java implementation in place of vardict.pl)
Quick start
-----------
Make sure the VarDict folder (scripts ``vardict.pl``, ``vardict``, ``testsomatic.R``, ``teststrandbias.R``, ``var2vcf_valid.pl`` and ``var2vcf_paired.pl``) is in path before running the following commands.
- Running in single sample mode::
AF_THR="0.01" # minimum allele frequency
vardict -G /path/to/hg19.fa -f $AF_THR -N sample_name -b /path/to/my.bam -c 1 -S 2 -E 3 -g 4 /path/to/my.bed | teststrandbias.R | var2vcf_valid.pl -N sample_name -E -f $AF_THR
- Paired variant calling::
AF_THR="0.01" # minimum allele frequency
vardict -G /path/to/hg19.fa -f $AF_THR -N tumor_sample_name -b "/path/to/tumor.bam|/path/to/normal.bam" -c 1 -S 2 -E 3 -g 4 /path/to/my.bed | testsomatic.R | var2vcf_paired.pl -N "tumor_sample_name|normal_sample_name" -f $AF_THR
Contributors
------------
- `Zhongwu Lai`_, AstraZeneca
.. _Zhongwu Lai: https://github.com/zhongwulai
- `Miika Ahdesmaki`_, AstraZeneca
.. _Miika Ahdesmaki: https://github.com/mjafin
- `Brad Chapman`_, Harvard School of Public Health
.. _Brad Chapman: https://github.com/chapmanb
License
-------
The code is freely available under the `MIT license`_.
.. _MIT license: http://www.opensource.org/licenses/mit-license.html