TY  - JOUR
AU  - Xu, J
AU  - Falconer, C
AU  - Nguyen, Q
AU  - Crawford, J
AU  - McKinnon, BD
AU  - Mortlock, S
AU  - Senabouth, A
AU  - Andersen, S
AU  - Chiu, HS
AU  - Jiang, L
AU  - Palpant, NJ
AU  - Yang, J
AU  - Mueller, MD
AU  - Hewitt, AW
AU  - Pebay, A
AU  - Montgomery, GW
AU  - Powell, JE
AU  - Coin, LJM
Y2  - 2020/10/12
Y1  - 2019/12/19
SN  - 1474-760X
UR  - http://hdl.handle.net/11343/247063
AB  - 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.
LA  - English
PB  - BMC
T1  - Genotype-free demultiplexing of pooled single-cell RNA-seq
DO  - 10.1186/s13059-019-1852-7
IS  - Genome Biology
VL  - 20
IS  - 1
L1  - /bitstream/handle/11343/247063/PMC6921391.pdf?sequence=1&isAllowed=y
ER  -