Back to search

Article

Deconvolution of omics data in Python with Deconomix – cellular compositions, cell-type specific gene regulation, and background contributions

2024-12-03

Abstract excerpt

<h4>Summary</h4> Gene expression profiles of heterogeneous bulk samples contain signals from multiple cell populations. Studying variations in their composition can help to identify cell populations relevant for disease. Moreover, analyses, such as the identification of differentially expressed genes, can be confounded by cellular composition, as differences in gene expression may arise from both variations in ce...

Topics

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

Identifiers and source

Literature Corpus work
979276ad-7a50-51e5-b7d3-767efa6cad3f
DOI
10.1101/2024.11.28.625894
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.
Deconvolution of omics data in Python with Deconomix – cellular compositions, cell-type specific gene regulation, and background contributionsDOI 10.1101/2024.11.28.625894
Select a neighboring publication to make it the new centre.