TSEE: an elastic embedding method to visualize the dynamic gene expression patterns of time series single-cell RNA sequencing data.

ABSTRACT:

Background

Time series single-cell RNA sequencing (scRNA-seq) data are emerging. However, the analysis of time series scRNA-seq data could be compromised by 1) distortion created by assorted sources of data collection and generation across time samples and 2) inheritance of cell-to-cell variations by stochastic dynamic patterns of gene expression. This calls for the development of an algorithm able to visualize time series scRNA-seq data in order to reveal latent structures and uncover dynamic transition processes.

Results

In this study, we propose an algorithm, termed time series elastic embedding (TSEE), by incorporating experimental temporal information into the elastic embedding (EE) method, in order to visualize time series scRNA-seq data. TSEE extends the EE algorithm

SUBMITTER: An S 

PROVIDER: S-EPMC6456934 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature