Genotype-free demultiplexing of pooled single-cell RNA-seq

被引：47

作者：

Xu, Jun ^{[1
]}

Falconer, Caitlin ^{[2
]}

Nguyen, Quan ^{[2
]}

Crawford, Joanna ^{[2
]}

McKinnon, Brett D. ^{[2
,5
]}

Mortlock, Sally ^{[2
]}

Senabouth, Anne ^{[4
]}

Andersen, Stacey ^{[1
,2
]}

Chiu, Han Sheng ^{[2
]}

Jiang, Longda ^{[2
]}

Palpant, Nathan J. ^{[1
,2
]}

Yang, Jian ^{[2
,10
]}

Mueller, Michael D. ^{[5
]}

Hewitt, Alex W. ^{[7
,8
,9
]}

Pebay, Alice ^{[6
,7
,8
]}

Montgomery, Grant W. ^{[1
,2
]}

Powell, Joseph E. ^{[3
,4
]}

Coin, Lachlan J. M. ^{[1
,2
,11
,12
,13
]}

机构：

[1] Univ Queensland, Genome Innovat Hub, 306 Carmody Rd, Brisbane, Qld 4072, Australia

[2] Univ Queensland, Inst Mol Biosci, 306 Carmody Rd, Brisbane, Qld 4072, Australia

[3] Univ New South Wales, Sch Med Sci, UNSW Cellular Genom Futures Inst, Sydney, NSW 2052, Australia

[4] Garvan Inst, Garvan Weizmann Ctr Cellular Genom, 384 Victoria St, Sydney, NSW 2010, Australia

[5] Berne Univ Hosp, Dept Obstet & Gynaecol, CH-3012 Bern, Switzerland

[6] Univ Melbourne, Dept Anat & Neurosci, Parkville, Vic 3010, Australia

[7] Univ Melbourne, Dept Surg, Parkville, Vic 3010, Australia

[8] Royal Victorian Eye & Ear Hosp, Ctr Eye Res Australia, East Melbourne 3002, Australia

[9] Univ Tasmania, Sch Med, Menzies Inst Med Res, Hobart, Tas 7005, Australia

[10] Wenzhou Med Univ, Inst Adv Res, Wenzhou 325027, Zhejiang, Peoples R China

[11] Univ Melbourne, Dept Microbiol & Immunol, Parkville, Vic 3010, Australia

[12] Univ Melbourne, Dept Clin Pathol, Parkville, Vic 3010, Australia

[13] Imperial Coll London, Dept Infect Dis, London W2 1NY, England

来源：

GENOME BIOLOGY | 2019年 / 20卷 / 01期

基金：

英国医学研究理事会; 澳大利亚研究理事会;

关键词：

scSplit; scRNA-seq; Demultiplexing; Machine learning; Unsupervised; Hidden Markov Model; Expectation-maximization; Genotype-free; Allele fraction; Doublets;

D O I：

10.1186/s13059-019-1852-7

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling. We introduce scSplit which utilizes genetic differences inferred from scRNA-seq data alone to demultiplex pooled samples. scSplit also enables mapping clusters to original samples. Using simulated, merged, and pooled multi-individual datasets, we show that scSplit prediction is highly concordant with demuxlet predictions and is highly consistent with the known truth in cell-hashing dataset.

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