tutorial arrow
×
Create your own tool library
Bookmark tools and put favorites into folders to find them easily.

VarMatch

Uses for the variant matching problem. VarMatch is able to detect more matches than either the normalization or decomposition algorithms on tested datasets. It is robust to different representation of complex variants and is particularly effective in low complexity regions or those dense in variants. It also implements different optimization criteria, such as edit distance, that can improve robustness to different variant representations. Finally, the VarMatch software provides summary statistics, annotations, and visualizations that are useful for understanding callers’ performance

User report

tutorial arrow
×
Vote up tools and offer feedback
Give value to tools and make your expertise visible
Sort by:

1 user review

1 user review

0x0101's avatar image

0x0101

It's especially useful to find high-quality variants by intersecting the results of different variant calling tools. For instance, you can predict variants using Freebayes and GATK, and then use VarMatch to find high-quality variants that are supported by both tools.

VarMatch forum

tutorial arrow
×
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.

No open topic.

VarMatch versioning

tutorial arrow
×
Upload and version your source code
Get a DOI for each update to improve tool traceability. Archive your releases so the community can easily visualize progress on your work.

No versioning.

VarMatch classification

VarMatch specifications

Software type:
Package/Module
Restrictions to use:
None
Operating system:
Unix/Linux, Mac OS, Windows
License:
GNU General Public License version 3.0
Stability:
Stable
Maintained:
Yes
Interface:
Command line interface
Input format:
VCF
Programming languages:
C++, Python
Computer skills:
Advanced
Requirements:
GCC, matplotlib
Source code URL:
https://github.com/medvedevgroup/varmatch

VarMatch support

Documentation

Maintainer

  • Chen Sun <>

Credits

tutorial arrow
×
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.

Publications

Institution(s)

Department of Computer Science and Engineering, The Pennsylvania State University, PA, USA; Department of Biochemistry and Molecular Biology, The Pennsylvania State University, PA, USA; Genome Sciences Institute at the Huck, The Pennsylvania State University, PA, USA

Funding source(s)

This work has been supported in part by NSF awards DBI-1356529, CCF-1439057, IIS-1453527, and IIS-1421908.

Link to literature

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.