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Valid Post-clustering Differential Analysis for Single-Cell RNA-Seq.

ABSTRACT: Single-cell computational pipelines involve two critical steps: organizing cells (clustering) and identifying the markers driving this organization (differential expression analysis). State-of-the-art pipelines perform differential analysis after clustering on the same dataset. We observe that because clustering "forces" separation, reusing the same dataset generates artificially low p values and hence false discoveries. We introduce a valid post-clustering differential analysis framework, which corrects for this problem. We provide software at https://github.com/jessemzhang/tn_test.

SUBMITTER: Zhang JM

PROVIDER: S-EPMC7202736 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Valid Post-clustering Differential Analysis for Single-Cell RNA-Seq.

Zhang Jesse M JM Kamath Govinda M GM Tse David N DN

Cell systems 20190911 4

Single-cell computational pipelines involve two critical steps: organizing cells (clustering) and identifying the markers driving this organization (differential expression analysis). State-of-the-art pipelines perform differential analysis after clustering on the same dataset. We observe that because clustering "forces" separation, reusing the same dataset generates artificially low p values and hence false discoveries. We introduce a valid post-clustering differential analysis framework, which ...[more]

PMID: 31521605

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