CONICS integrates scRNA-seq with DNA sequencing to map gene expression to tumor sub-clones

Bioinformatics. 2018 Sep 15;34(18):3217-3219. doi: 10.1093/bioinformatics/bty316.

Abstract

Motivation: Single-cell RNA-sequencing (scRNA-seq) has enabled studies of tissue composition at unprecedented resolution. However, the application of scRNA-seq to clinical cancer samples has been limited, partly due to a lack of scRNA-seq algorithms that integrate genomic mutation data.

Results: To address this, we present.

Conics: COpy-Number analysis In single-Cell RNA-Sequencing. CONICS is a software tool for mapping gene expression from scRNA-seq to tumor clones and phylogenies, with routines enabling: the quantitation of copy-number alterations in scRNA-seq, robust separation of neoplastic cells from tumor-infiltrating stroma, inter-clone differential-expression analysis and intra-clone co-expression analysis.

Availability and implementation: CONICS is written in Python and R, and is available from https://github.com/diazlab/CONICS.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

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

MeSH terms

  • Algorithms
  • Gene Expression Profiling / methods*
  • Humans
  • Neoplasms / genetics*
  • RNA, Small Cytoplasmic*
  • Sequence Analysis, DNA / methods
  • Sequence Analysis, RNA / methods
  • Single-Cell Analysis / methods*
  • Software*

Substances

  • RNA, Small Cytoplasmic