DCARS: Differential correlation across ranked samples

Shila Ghazanfar, Dario Strbenac, John T. Ormerod, Jean Y. H. Yang, Ellis Patrick
2018 · doi:10.1101/303735
preprint OA: closed
📄 Open PDF View at publisher
⚙ AI-generated summary by claude@2026-06, 2026-06-12 ⓘ

This paper introduces DCARS, a novel method for identifying differential correlations between genes in ranked samples, enabling robust discovery of biologically relevant associations.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

Abstract

ABSTRACT Genes act as a system and not in isolation. Thus, it is important to consider coordinated changes of gene expression rather than single genes when investigating biological phenomena such as the aetiology of cancer. We have developed an approach for quantifying how changes in the association between pairs of genes may inform patient prognosis called Differential Correlation across Ranked Samples (DCARS). Modelling gene correlation across a continuous sample ranking does not require the classification of patients into ‘good’ or ‘poor’ prognosis groups and can identify differences in gene correlation across early, mid or late stages of survival outcome. When we evaluated DCARS against the typical Fisher Z-transformation test for differential correlation, as well as a typical approach testing for interaction within a linear model, on real TCGA data, DCARS significantly ranked gene pairs containing known cancer genes more highly across a number of cancers. Similar results are found with our simulation study. DCARS was applied to 13 cancers datasets in TCGA, revealing a number of distinct relationships for which survival ranking was found to be associated with a change in correlation between genes. Furthermore, we demonstrated that DCARS can be used in conjunction with network analysis techniques to extract biological meaning from multilayered and complex data. Availability: https://github.com/shazanfar/DCARS .

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

References (26)

Source provenance

crossref
last seen: 2026-05-21T01:00:08.417666+00:00
europepmc
last seen: 2026-05-19T01:45:01.086888+00:00