title: Integrating and mining the chromatin landscape of cell-type specificity using self-organizing maps.
abstract: We tested whether self-organizing maps (SOMs) could be used to effectively integrate, visualize, and mine diverse genomics data types, including complex chromatin signatures. A fine-grained SOM was trained on 72 ChIP-seq histone modifications and DNase-seq data sets from six biologically diverse cell lines studied by The ENCODE Project Consortium. We mined the resulting SOM to identify chromatin signatures related to sequence-specific transcription factor occupancy, sequence motif enrichment, and biological functions. To highlight clusters enriched for specific functions such as transcriptional promoters or enhancers, we overlaid onto the map additional data sets not used during training, such as ChIP-seq, RNA-seq, CAGE, and information on cis-acting regulatory modules from the literature. We used the SOM to parse known transcriptional enhancers according to the cell-type-specific chromatin signature, and we further corroborated this pattern on the map by EP300 (also known as p300) occupancy. New candidate cell-type-specific enhancers were identified for multiple ENCODE cell types in this way, along with new candidates for ubiquitous enhancer activity. An interactive web interface was developed to allow users to visualize and custom-mine the ENCODE SOM. We conclude that large SOMs trained on chromatin data from multiple cell types provide a powerful way to identify complex relationships in genomic data at user-selected levels of granularity.
authors.affiliation: Department of Developmental and Cell Biology, University of California, Irvine, California 92697, USA;
authors.forename: Ali
authors.initials: A
authors.lastname: Mortazavi
authors.forename: Shirley
authors.initials: S
authors.lastname: Pepke
authors.forename: Camden
authors.initials: C
authors.lastname: Jansen
authors.forename: Georgi K
authors.initials: GK
authors.lastname: Marinov
authors.forename: Jason
authors.initials: J
authors.lastname: Ernst
authors.forename: Manolis
authors.initials: M
authors.lastname: Kellis
authors.forename: Ross C
authors.initials: RC
authors.lastname: Hardison
authors.forename: Richard M
authors.initials: RM
authors.lastname: Myers
authors.forename: Barbara J
authors.initials: BJ
authors.lastname: Wold
mesh_terms: D000465:Algorithms; D002460:Cell Line; D002843:Chromatin / Q000235:genetics* / Q000378:metabolism*; D002874:Chromosome Mapping; D019295:Computational Biology; D057225:Data Mining; D063990:Gene Ontology; D006657:Histones / Q000235:genetics* / Q000378:metabolism*; D061307:Human Umbilical Vein Endothelial Cells; D006801:Humans; D020014:K562 Cells; D011401:Promoter Regions, Genetic; D014157:Transcription Factors / Q000235:genetics*; D014584:User-Computer Interface
chemical_list: D002843:Chromatin; D006657:Histones; D014157:Transcription Factors