Question: Unsupervised clustering of super-enhancers from Chip Seq data generated from ROSE
gravatar for Researcher
11 days ago by
Researcher50 wrote:

Hi All, I have ranked my chip-seq peaks and calculated the probable super enhancers using ROSE for my samples from different subtypes of cancer. Now I want to perform unsupervised clustering based on enriched SE regions to see whether the samples from same cancer subtype cluster together or not. Can anybody please guide me how can I do this? Have someone done this before? Any help or recommendations will be highly appreciated. Thanks

ADD COMMENTlink written 11 days ago by Researcher50

Nothing special to be done. Follow the usual steps: Get a count matrix for the entire ChIP-seq dataset (all peaks), normalize e.g. with TMM from edgeR(please not RPKM), filter for the regions of interest, transform to Z-scale and then plug into hclust. I would start with ward.D2 as the agglomeration method and see if things look meaningful. I recommend ComplexHeatmap which has many convenience functions for clustering/visualization/plotting.

ADD REPLYlink modified 11 days ago • written 11 days ago by ATpoint24k

Thanks ATpoint for your reply. But I am wondering about the sites that have different start and end loci but are overlapping. How should I deal with that?

ADD REPLYlink written 11 days ago by Researcher50
Please log in to add an answer.


Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1520 users visited in the last hour