Clust solves what we perceive as the biggest problem in gene co-expression clustering.

Clust extracts tight and distinct clusters of co-expressed genes from one or more gene expression datasets. Clust automatically filters out genes that do not form quality clusters.

Clust follows an automatic pipeline of sophisticated steps of draft clustering, cluster evaluation and selection, and cluster optimisation and completion (summarised in the figure below).

Clust is freely available as easy-to-install easy-to-use package at:

Clust outperforms mainstream gene expression methods as demonstrated by comparison over 100 datasets assessed by eight different cluster validation metrics. Details are in our pre-print manuscript.

Clust has recently been accepted for publication in Genome Biology (In Press).

Until the Genome Biology paper is released, please cite this pre-print if you use clust:

Basel Abu-Jamous and Steven Kelly (2018) Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data. bioRxiv 221309; doi:





Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s