MetaCell: Analysis of Single-cell RNA-seq Data Using K-nn Graph Partitions

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2019 Oct 13

PMID 31604482

Citations 166

Authors

Yael Baran

Akhiad Bercovich

Arnau Sebe-Pedros

Yaniv Lubling

Amir Giladi

Elad Chomsky

Zohar Meir

Michael Hoichman

Aviezer Lifshitz

Amos Tanay

Affiliations

Soon will be listed here.

Abstract

scRNA-seq profiles each represent a highly partial sample of mRNA molecules from a unique cell that can never be resampled, and robust analysis must separate the sampling effect from biological variance. We describe a methodology for partitioning scRNA-seq datasets into metacells: disjoint and homogenous groups of profiles that could have been resampled from the same cell. Unlike clustering analysis, our algorithm specializes at obtaining granular as opposed to maximal groups. We show how to use metacells as building blocks for complex quantitative transcriptional maps while avoiding data smoothing. Our algorithms are implemented in the MetaCell R/C++ software package.

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