Back to search

Article

SIEVEseq: One-stop differential expression, variability, and skewness analyses using RNA-Seq data

2024-04-13

Abstract excerpt

RNA-Seq data analysis is commonly biased towards detecting differentially expressed genes and insufficiently conveys the complexity of gene expression changes between biological conditions. This bias arises because discrete count models cannot fully and independently parameterize the mean, variance, and skewness of gene expression distributions. Therefore, a unified statistical framework that simultaneously tests...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
3320c09e-1363-573c-b77a-d8fef2b1ecef
DOI
10.1101/2024.04.09.588804
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
SIEVEseq: One-stop differential expression, variability, and skewness analyses using RNA-Seq dataDOI 10.1101/2024.04.09.588804
Select a neighboring publication to make it the new centre.