SAMstrt: statistical test for differential expression in single-cell transcriptome with spike-in normalization | Zendy

Shintaro Katayama | Zendy; Virpi Töhönen | Zendy; Sten Linnarsson | Zendy; Juha Kere | Zendy

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SAMstrt: statistical test for differential expression in single-cell transcriptome with spike-in normalization

Author(s) -

Shintaro Katayama,

Virpi Töhönen,

Sten Linnarsson,

Juha Kere

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btt511

Subject(s) - normalization (sociology) , transcriptome , computer science , statistical analysis , statistical hypothesis testing , computational biology , biology , gene expression , statistics , genetics , gene , mathematics , sociology , anthropology

Recent transcriptome studies have revealed that total transcript numbers vary by cell type and condition; therefore, the statistical assumptions for single-cell transcriptome studies must be revisited. SAMstrt is an extension code for SAMseq, which is a statistical method for differential expression, to enable spike-in normalization and statistical testing based on the estimated absolute number of transcripts per cell for single-cell RNA-seq methods.

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