Combinatorial prediction of marker panels from single‐cell transcriptomic data. Issue 10 (24th October 2019)

• Record Type: Journal Article
• Authors: Delaney, Conor; Schnell, Alexandra; Cammarata, Louis V; Yao‐Smith, Aaron; Regev, Aviv; Kuchroo, Vijay K; Singer, Meromit
• Is Part Of: Molecular systems biology. Volume 15:Issue 10(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-10-24
• Subjects: cell types -- computational biology -- data analysis -- marker panel -- single‐cell RNA‐seq; Molecular biology -- Periodicals; Systems biology -- Periodicals; 572.8
• DOI: 10.15252/msb.20199005
• Languages: English
• ISSNs: 1744-4292

Abstract

Abstract: Single‐cell transcriptomic studies are identifying novel cell populations with exciting functional roles in various in vivo contexts, but identification of succinct gene marker panels for such populations remains a challenge. In this work, we introduce COMET, a computational framework for the identification of candidate marker panels consisting of one or more genes for cell populations of interest identified with single‐cell RNA‐seq data. We show that COMET outperforms other methods for the identification of single‐gene panels and enables, for the first time, prediction of multi‐gene marker panels ranked by relevance. Staining by flow cytometry assay confirmed the accuracy of COMET's predictions in identifying marker panels for cellular subtypes, at both the single‐ and multi‐gene levels, validating COMET's applicability and accuracy in predicting favorable marker panels from transcriptomic input. COMET is a general non‐parametric statistical framework and can be used as‐is on various high‐throughput datasets in addition to single‐cell RNA‐sequencing data. COMET is available for use via a web interface (http://www.cometsc.com/ ) or a stand‐alone software package (https://github.com/MSingerLab/COMETSC ). Synopsis: COMET is a computational tool for marker‐panel selection from single‐cell RNA‐seq data. It generates ranked predictions of single‐ and multiple‐gene marker panels for a cell population of interest. COMET is a computational tool for combinatorial prediction of marker panels from single‐cell transcriptomic data. COMET's statistical framework enables controlling for specificity and sensitivity in predicted marker panels. Staining by flow‐cytometry validates that COMET identifies novel and favorable single‐ and multi‐gene marker panels for cellular subtypes. COMET is available via a web interface (http://www.cometsc.com/ ) or downloadable software package (https://github.com/MSingerLab/COMETSC ). Abstract : COMET is a computational tool for marker‐panel selection from single‐cell RNA‐seq data. It generates ranked predictions of single‐ and multiple‐gene marker panels for a cell population of interest.