Back to search

Article

A statistical framework for disease classification with scRNA-Seq Data

2026-08-25

Abstract excerpt

Motivation Bulk RNA-sequencing based disease classification obscures cell-type specific signals by aggregating gene expression across heterogeneous tissues. Although single-cell RNA-seq tackles this limitation, summarizing and deriving patient-level predictors while retaining biological interpretability remains challenging. Standard sparse methods, such as lasso, often select arbitrary scattered gene sets without...

Topics

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

Identifiers and source

Literature Corpus work
1623f664-c36d-558d-8ec1-4306ecf60379
DOI
10.64898/2026.08.21.746294
Open publication

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

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.
A statistical framework for disease classification with scRNA-Seq DataDOI 10.64898/2026.08.21.746294
Select a neighboring publication to make it the new centre.