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SV-M specifications

Information


Unique identifier OMICS_00101
Name SV-M
Alternative name Structural Variant Machine
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C, C++
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Dominik Grimm <>

Publication for Structural Variant Machine

SV-M citations

 (2)
library_books

Performance evaluation of indel calling tools using real short read data

2015
PMCID: 4545535
PMID: 26286629
DOI: 10.1186/s40246-015-0042-2

[…] are then clustered or aligned by de novo assembly to determine indels (fig.  ()). tools in this category include pindel [] that uses a pattern growth approach to detect breakpoints of indels, and sv-m [] that performs a discriminative classification based on features of split read alignment profiles and then filters the result against empirically derived training set data to reduce […]

library_books

Century scale Methylome Stability in a Recently Diverged Arabidopsis thaliana Lineage

2015
PMCID: 4287485
PMID: 25569172
DOI: 10.1371/journal.pgen.1004920

[…] only tools based on split read alignments and assemblies are capable of pinpointing sv breakpoints down to the exact base pair. programs that were used include pindel v2.4t , delly v0.0.9 , sv-m v0.1 and a custom local de novo assembly pipeline targeted towards sequencing gaps (described below). we reported deletions and insertions from all tools, and additionally inversions […]


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SV-M institution(s)
Machine Learning and Computational Biology Research Group, Max Planck Institute for Developmental Biology and Max Planck Institute for Intelligent Systems, Tübingen, Germany; Department of Molecular Biology, Max Planck Institute for Developmental Biology, Tübingen, Germany; Center for Bioinformatics, Eberhard Karls Universität, Tübingen, Germany
SV-M funding source(s)
Supported by Transnational Plant Alliance for Novel Technologies – Towards Implementing the Knowledge-based Bioeconomy in Europe (PLANT-KBBE) project Transcriptional Networks and Their Evolution in the Brassicaceae (TRANSNET), funded by the Bundesministerium für Bildung und Forschung, by a Gottfried Wilhelm Leibniz Award of the Deutsche Forschungsgemeinschaft, and the Max Planck Society.

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