Consensus clustering applied to multi-omics disease subtyping.

ABSTRACT:

Background

Facing the diversity of omics data and the difficulty of selecting one result over all those produced by several methods, consensus strategies have the potential to reconcile multiple inputs and to produce robust results.

Results

Here, we introduce ClustOmics, a generic consensus clustering tool that we use in the context of cancer subtyping. ClustOmics relies on a non-relational graph database, which allows for the simultaneous integration of both multiple omics data and results from various clustering methods. This new tool conciliates input clusterings, regardless of their origin, their number, their size or their shape. ClustOmics implements an intuitive and flexible strategy, based upon the idea of evidence accumulation clustering. ClustOmics computes co-occu

SUBMITTER: Briere G 

PROVIDER: S-EPMC8259015 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature