Spatial Clustering of Multivariate Genomic and Epigenomic Information

The combination of fully sequence genomes and new technologies for high density arrays and ultra-rapid sequencing enables the mapping of generegulatory and epigenetics marks on a global scale. This new experimental methodology was recently applied to map multiple histone marks and genomic factors, characterizing patterns of genome organization and discovering interactions among processes of epigenetic reprogramming during cellular differentiation. The new data poses a significant computational challenge in both size and statistical heterogeneity. Understanding it collectively and without bias remains an open problem. Here we introduce spatial clustering - a new unsupervised clustering methodology for dissection of large, multi-track genomic and epigenomic data sets into a spatially organized set of distinct combinatorial behaviors. We develop a probabilistic algorithm that finds spatial clustering solutions by learning an HMM model and inferring the most likely genomic layout of cluste...

• Type: Conference
• Year: 2009
• Where: RECOMB
• Authors: Rami Jaschek, Amos Tanay
• Keywords: Computational Biology, RECOMB 2009, Spatial Clustering, Spatial Clustering Solutions, Unsupervised Clustering Methodology