ILoReg: a tool for high-resolution cell population identification from single-cell RNA-seq data | Zendy

Johannes Smolander | Zendy; Sini Junttila | Zendy; Mikko S. Venäläinen | Zendy; Laura L. Elo | Zendy

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ILoReg: a tool for high-resolution cell population identification from single-cell RNA-seq data

Author(s) -

Johannes Smolander,

Sini Junttila,

Mikko S. Venäläinen,

Laura L. Elo

Publication year - 2020

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/btaa919

Subject(s) - cluster analysis , computer science , population , bioconductor , visualization , data mining , identification (biology) , artificial intelligence , pattern recognition (psychology) , biology , genetics , demography , botany , sociology , gene

Single-cell RNA-seq allows researchers to identify cell populations based on unsupervised clustering of the transcriptome. However, subpopulations can have only subtle transcriptomic differences and the high dimensionality of the data makes their identification challenging.

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