IKAP-Identifying K mAjor cell Population groups in single-cell RNA-sequencing analysis.

ABSTRACT:

Background

In single-cell RNA-sequencing analysis, clustering cells into groups and differentiating cell groups by differentially expressed (DE) genes are 2 separate steps for investigating cell identity. However, the ability to differentiate between cell groups could be affected by clustering. This interdependency often creates a bottleneck in the analysis pipeline, requiring researchers to repeat these 2 steps multiple times by setting different clustering parameters to identify a set of cell groups that are more differentiated and biologically relevant.

Findings

To accelerate this process, we have developed IKAP-an algorithm to identify major cell groups and improve differentiating cell groups by systematically tuning parameters for clustering. We demonstrate that, with d

SUBMITTER: Chen YC 

PROVIDER: S-EPMC6771546 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature