pyNBS: a Python implementation for network-based stratification of tumor mutations

Abstract Summary We present pyNBS: a modularized Python 2.7 implementation of the network-based stratification (NBS) algorithm for stratifying tumor somatic mutation profiles into molecularly and clinically relevant subtypes. In addition to release of the software, we benchmark its key parameters an...

Full description

Saved in:
Bibliographic Details
Published inBioinformatics Vol. 34; no. 16; pp. 2859 - 2861
Main Authors Huang, Justin K, Jia, Tongqiu, Carlin, Daniel E, Ideker, Trey
Format Journal Article
LanguageEnglish
Published England Oxford University Press 15.08.2018
Subjects
Applications Notes
Online AccessGet full text
ISSN1367-4803
1367-4811
1460-2059
1367-4811
DOI10.1093/bioinformatics/bty186

Cover

More Information
Summary:Abstract Summary We present pyNBS: a modularized Python 2.7 implementation of the network-based stratification (NBS) algorithm for stratifying tumor somatic mutation profiles into molecularly and clinically relevant subtypes. In addition to release of the software, we benchmark its key parameters and provide a compact cancer reference network that increases the significance of tumor stratification using the NBS algorithm. The structure of the code exposes key steps of the algorithm to foster further collaborative development. Availability and implementation The package, along with examples and data, can be downloaded and installed from the URL https://github.com/idekerlab/pyNBS.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/bty186