Investigating higher-order interactions in single-cell data with scHOT

被引：42

作者：

Ghazanfar, Shila ^{[1
]}

Lin, Yingxin ^{[2
,3
]}

Su, Xianbin ^{[4
,5
]}

Lin, David Ming ^{[6
]}

Patrick, Ellis ^{[2
,7
]}

Han, Ze-Guang ^{[4
,5
]}

Marioni, John C. ^{[1
,8
,9
]}

Yang, Jean Yee Hwa ^{[2
,3
]}

机构：

[1] Univ Cambridge, Canc Res UK Cambridge Inst, Cambridge, England

[2] Univ Sydney, Sch Math & Stat, Sydney, NSW, Australia

[3] Univ Sydney, Charles Perkins Ctr, Sydney, NSW, Australia

[4] Shanghai Jiao Tong Univ, Shanghai Ctr Syst Biomed, Minist Educ, Key Lab Syst Biomed, Shanghai, Peoples R China

[5] Shanghai Jiao Tong Univ, Shanghai Ctr Syst Biomed, Collaborat Innovat Ctr Syst Biomed, Shanghai, Peoples R China

[6] Cornell Univ, Dept Biomed Sci, Ithaca, NY USA

[7] Westmead Inst Med Res, Westmead, NSW, Australia

[8] European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge, England

[9] Wellcome Sanger Inst, Wellcome Genome Campus, Cambridge, England

来源：

NATURE METHODS | 2020年 / 17卷 / 08期

基金：

中国国家自然科学基金; 澳大利亚研究理事会; 澳大利亚国家健康与医学研究理事会;

关键词：

GENE-EXPRESSION; FATE DECISIONS; ARRESTIN; IDENTIFICATION; DYNAMICS; RECEPTOR; TISSUE;

D O I：

10.1038/s41592-020-0885-x

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Single-cell genomics has transformed our ability to examine cell fate choice. Examining cells along a computationally ordered 'pseudotime' offers the potential to unpick subtle changes in variability and covariation among key genes. We describe an approach, scHOT-single-cell higher-order testing-which provides a flexible and statistically robust framework for identifying changes in higher-order interactions among genes. scHOT can be applied for cells along a continuous trajectory or across space and accommodates various higher-order measurements including variability or correlation. We demonstrate the use of scHOT by studying coordinated changes in higher-order interactions during embryonic development of the mouse liver. Additionally, scHOT identifies subtle changes in gene-gene correlations across space using spatially resolved transcriptomics data from the mouse olfactory bulb. scHOT meaningfully adds to first-order differential expression testing and provides a framework for interrogating higher-order interactions using single-cell data. scHOT enables detection of changes in higher-order interactions in single-cell gene expression data.

引用

页码：799 / +

页数：22

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