Clust is a method for clustering data. We designed it with gene expression data in mind, but it can be applied to any data.
Clust automatically finds the optimal set of clusters in your dataset. You dataset could be a straight forward treatment-response type dataset, or it could be hundreds of different time-courses in dozens of species.
There is no need to pre-process your data Clust automatically detects and implements the correct pre-processing required. There is no need to preset the number of clusters clust finds this number. automatically. You can mix data from different technologies e.g. RNA-seq or microarrays. You can even mix data from from different species.
Clust has been designed to be used with OrthoFinder so that you can compare gene expression across species and across orthogroups with ease!
If you don’t want to install clust, you can run clust online here
Abu-Jamous B and Kelly S (2018) Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data. Genome Biology 19:172