Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis.

ABSTRACT:

Background

Dimensionality reduction is an indispensable analytic component for many areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality reduction can allow for effective noise removal and facilitate many downstream analyses that include cell clustering and lineage reconstruction. Unfortunately, despite the critical importance of dimensionality reduction in scRNA-seq analysis and the vast number of dimensionality reduction methods developed for scRNA-seq studies, few comprehensive comparison studies have been performed to evaluate the effectiveness of different dimensionality reduction methods in scRNA-seq.

Results

We aim to fill this critical knowledge gap by providing a comparative evaluation of a variety of commonly used dimensionality redu

SUBMITTER: Sun S 

PROVIDER: S-EPMC6902413 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature