Journal Article

Combinatorial prediction of marker panels from single‐cell transcriptomic data

Kuchroo, Vijay K, Schnell, Alexandra, Delaney, Conor, Cammarata, Louis V, Regev, Aviv, Yao‐Smith, Aaron, Singer, Meromit

2019

Overview

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 ). Graphical 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.

• Publisher: Nature Publishing Group UK,EMBO Press,John Wiley and Sons Inc,Springer Nature
• Subject: Animals / Biomarkers / cell types / Combinatorial analysis / Computational Biology / Computer applications / data analysis / EMBO09 / EMBO10 / Flow cytometry / Gene expression / Gene Expression Profiling - methods / Gene Expression Regulation / Gene sequencing / Genetic Markers / High-Throughput Nucleotide Sequencing / Identification / Identification methods / Laboratory animals / marker panel / Marker panels / Medical research / Method / Methods / Mice / Populations / Predictions / Ribonucleic acid / RNA / Sequence Analysis, RNA / Single-Cell Analysis - methods / single‐cell RNA‐seq / Software / Visualization