| Literature DB >> 29608663 |
Justin K Huang1, Tongqiu Jia2, Daniel E Carlin2, Trey Ideker1,2.
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.Entities:
Mesh:
Year: 2018 PMID: 29608663 PMCID: PMC6084608 DOI: 10.1093/bioinformatics/bty186
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937