Genotype-free demultiplexing of pooled single-cell RNA-seq.
Options
BORIS DOI
Date of Publication
December 19, 2019
Publication Type
Article
Division/Institute
Contributor
Xu, Jun | |
Falconer, Caitlin | |
Nguyen, Quan | |
Crawford, Joanna | |
Mortlock, Sally | |
Senabouth, Anne | |
Andersen, Stacey | |
Chiu, Han Sheng | |
Jiang, Longda | |
Palpant, Nathan J | |
Yang, Jian | |
Hewitt, Alex W | |
Pébay, Alice | |
Montgomery, Grant W | |
Powell, Joseph E | |
Coin, Lachlan J M |
Subject(s)
Series
Genome biology
ISSN or ISBN (if monograph)
1465-6906
Publisher
BioMed Central Ltd.
Language
English
Publisher DOI
PubMed ID
31856883
Uncontrolled Keywords
Description
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.
File(s)
File | File Type | Format | Size | License | Publisher/Copright statement | Content | |
---|---|---|---|---|---|---|---|
document.pdf | text | Adobe PDF | 2.61 MB | Attribution (CC BY 4.0) | published |