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

Authors :
Xu, J
Falconer, C
Nguyen, Q
Crawford, J
McKinnon, BD
Mortlock, S
Senabouth, A
Andersen, S
Chiu, HS
Jiang, L
Palpant, NJ
Yang, J
Mueller, MD
Hewitt, AW
Pebay, A
Montgomery, GW
Powell, JE
Coin, LJM
Xu, J
Falconer, C
Nguyen, Q
Crawford, J
McKinnon, BD
Mortlock, S
Senabouth, A
Andersen, S
Chiu, HS
Jiang, L
Palpant, NJ
Yang, J
Mueller, MD
Hewitt, AW
Pebay, A
Montgomery, GW
Powell, JE
Coin, LJM
Publication Year :
2019

Abstract

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. scSplit is ideally suited to samples without external genotype information and is available at: https://github.com/jon-xu/scSplit.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1315708441
Document Type :
Electronic Resource