Discovering monotonic stemness marker genes from time-series stem cell microarray data.

ABSTRACT:

Background

Identification of genes with ascending or descending monotonic expression patterns over time or stages of stem cells is an important issue in time-series microarray data analysis. We propose a method named Monotonic Feature Selector (MFSelector) based on a concept of total discriminating error (DEtotal) to identify monotonic genes. MFSelector considers various time stages in stage order (i.e., Stage One vs. other stages, Stages One and Two vs. remaining stages and so on) and computes DEtotal of each gene. MFSelector can successfully identify genes with monotonic characteristics.

Results

We have demonstrated the effectiveness of MFSelector on two synthetic data sets and two stem cell differentiation data sets: embryonic stem cell neurogenesis (ESCN) and embryonic s

SUBMITTER: Wang HW 

PROVIDER: S-EPMC4331716 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature