Machine learning and statistical methods for clustering single-cell RNA-sequencing data

Volume: 21, Issue: 4, Pages: 1209 - 1223
Published: Jun 27, 2019
Abstract
Single-cell RNAsequencing (scRNA-seq) technologies have enabled the large-scale whole-transcriptome profiling of each individual single cell in a cell population. A core analysis of the scRNA-seq transcriptome profiles is to cluster the single cells to reveal cell subtypes and infer cell lineages based on the relations among the cells. This article reviews the machine learning and statistical methods for clustering scRNA-seq transcriptomes...
Paper Details
Title
Machine learning and statistical methods for clustering single-cell RNA-sequencing data
Published Date
Jun 27, 2019
Volume
21
Issue
4
Pages
1209 - 1223
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.