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

Bioinformatics. 2018 Aug 15;34(16):2859-2861. doi: 10.1093/bioinformatics/bty186.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Humans
  • Mutation*
  • Neoplasms / genetics*
  • Sequence Analysis, DNA / statistics & numerical data
  • Software*