xCell: digitally portraying the tissue cellular heterogeneity landscape.

Abstract:

:Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/ .

journal_name

Genome Biol

journal_title

Genome biology

authors

Aran D,Hu Z,Butte AJ

doi

10.1186/s13059-017-1349-1

subject

Has Abstract

pub_date

2017-11-15 00:00:00

pages

220

issue

1

eissn

1474-7596

issn

1474-760X

pii

10.1186/s13059-017-1349-1

journal_volume

18

pub_type

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