Open Access Repository

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

Downloads

Downloads per month over past year

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 ORCID: 0000-0002-5123-5999, Pebay, A, Montgomery, GW, Powell, JE and Coin, LJM 2019 , 'Genotype-free demultiplexing of pooled single-cell RNA-seq' , Genome Biology, vol. 20, no. 1 , pp. 1-12 , doi: 10.1186/s13059-019-1852-7.

[img]
Preview
PDF (Published version)
138041 - Genoty...pdf | Download (2MB)

| Preview

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.

Item Type: Article
Authors/Creators:Xu, J and Falconer, C and Nguyen, Q and Crawford, J and McKinnon, BD and Mortlock, S and Senabouth, A and Andersen, S and Chiu, HS and Jiang, L and Palpant, NJ and Yang, J and Mueller, MD and Hewitt, AW and Pebay, A and Montgomery, GW and Powell, JE and Coin, LJM
Keywords: allele fraction, demultiplexing, doublets, expectation-maximization, genotype-free, Hidden Markov Model, machine learning, unsupervised, scRNA-seq, scSplit
Journal or Publication Title: Genome Biology
Publisher: BioMed Central Ltd.
ISSN: 1474-760X
DOI / ID Number: 10.1186/s13059-019-1852-7
Copyright Information:

© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to theCreative Commons license, and indicate if changes were made.

Related URLs:
Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page
TOP