Back to search

Article

snATAC-Express infers Gene Expression from Prioritized Chromatin Accessibility Peaks using Machine Learning

2025-07-25

Abstract excerpt

<h4>Background</h4> Single cell multi-omic investigation opens-up new opportunities to understand mechanisms of gene regulation. Existing methods for inferring transcript abundance from chromatin accessibility fail to prioritize the most relevant peaks and tend to assume positive associations between ATAC peaks and RNA counts. We hypothesize that gene regulation can be modeled as a function of combined positive a...

Topics

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

Identifiers and source

Literature Corpus work
4dc1ccff-9322-5d2a-ab24-d561b2ed52dc
DOI
10.1101/2025.07.25.666784
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.
snATAC-Express infers Gene Expression from Prioritized Chromatin Accessibility Peaks using Machine LearningDOI 10.1101/2025.07.25.666784
Select a neighboring publication to make it the new centre.