Back to search

Article

CausalCell: applying causal discovery to single-cell analyses

2022-08-19

Abstract excerpt

<h4>ABSTRACT</h4> Correlation between objects does not answer many scientific questions because of the lack of causal but the excess of spurious information and is prone to happen by coincidence. Causal discovery infers causal relationships from data upon conditional independence test between objects without prior assumptions (e.g., variables have linear relationships and data follow the Gaussian distribution). C...

Topics

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

Identifiers and source

Literature Corpus work
171bdccc-8624-5d64-a906-2e71cd2ab6c4
DOI
10.1101/2022.08.19.504494
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.
CausalCell: applying causal discovery to single-cell analysesDOI 10.1101/2022.08.19.504494
Select a neighboring publication to make it the new centre.