A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data.

ABSTRACT:

Background

Identifying differentially expressed genes between the same or different species is an urgent demand for biological and medical research. For RNA-seq data, systematic technical effects and different sequencing depths are usually encountered when conducting experiments. Normalization is regarded as an essential step in the discovery of biologically important changes in expression. The present methods usually involve normalization of the data with a scaling factor, followed by detection of significant genes. However, more than one scaling factor may exist because of the complexity of real data. Consequently, methods that normalize data by a single scaling factor may deliver suboptimal performance or may not even work.The development of modern machine learning techniques ha

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC8234728 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature