Robust partial reference-free cell composition estimation from tissue expression | Zendy

Ziyi Li | Zendy; Zhenxing Guo | Zendy; Ying Cheng | Zendy; Peng Jin | Zendy; Hao Wu | Zendy

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Robust partial reference-free cell composition estimation from tissue expression

Author(s) -

Ziyi Li,

Zhenxing Guo,

Ying Cheng,

Peng Jin,

Hao Wu

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/btaa184

Subject(s) - bioconductor , computer science , composition (language) , sorting , estimation , computational biology , data mining , algorithm , biology , gene , genetics , linguistics , philosophy , management , economics

In the analysis of high-throughput omics data from tissue samples, estimating and accounting for cell composition have been recognized as important steps. High cost, intensive labor requirements and technical limitations hinder the cell composition quantification using cell-sorting or single-cell technologies. Computational methods for cell composition estimation are available, but they are either limited by the availability of a reference panel or suffer from low accuracy.

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