Publication

Power analysis of single-cell RNA-sequencing experiments

View document

Bibliographic Details
Summary:Single-cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, thereby revealing new cell types and providing insights into developmental processes and transcriptional stochasticity. A key question is how the variety of available protocols compare in terms of their ability to detect and accurately quantify gene expression. Here, we assessed the protocol sensitivity and accuracy of many published data sets, on the basis of spike-in standards and uniform data processing. For our workflow, we developed a flexible tool for counting the number of unique molecular identifiers (https://github.com/vals/umis/). We compared 15 protocols computationally and 4 protocols experimentally for batch-matched cell populations, in addition to investigating the effects of spike-in molecular degradation. Our analysis provides an integrated framework for comparing scRNA-seq protocols.
Main Authors:Svensson, Valentine
Other Authors:Natarajan, Kedar Nath; Ly, Lam-Ha; Miragaia, Ricardo J.; Labalette, Charlotte; Macaulay, Iain C.; Cvejic, Ana; Teichmann, Sarah A.
Subject:Gene expression RNA sequencing Transcriptomics
Year:2017
Country:Portugal
Document type:article
Access type:restricted access
Associated institution:Universidade do Minho
Language:English
Origin:RepositóriUM - Universidade do Minho

Similar Items

Funded activities

Loading funded projects...

Similar Items