title: Choosing panels of genomics assays using submodular optimization.
abstract: Due to the high cost of sequencing-based genomics assays such as ChIP-seq and DNase-seq, the epigenomic characterization of a cell type is typically carried out using a small panel of assay types. Deciding a priori which assays to perform is, thus, a critical step in many studies. We present the submodular selection of assays (SSA), a method for choosing a diverse panel of genomic assays that leverages methods from submodular optimization. More generally, this application serves as a model for how submodular optimization can be applied to other discrete problems in biology.
authors.affiliation: Department of Electrical Engineering, University of Washington, Seattle, WA, USA.
authors.forename: Kai
authors.initials: K
authors.lastname: Wei
authors.affiliation: Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
authors.forename: Maxwell W
authors.initials: MW
authors.lastname: Libbrecht
authors.affiliation: Department of Electrical Engineering, University of Washington, Seattle, WA, USA.
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Bilmes
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle, WA, USA. william-noble@uw.edu.
authors.forename: William Stafford
authors.identifier: 0000-0001-7283-4715
authors.initials: WS
authors.lastname: Noble
mesh_terms: D001665:Binding Sites; D047369:Chromatin Immunoprecipitation; D030561:Databases, Nucleic Acid; D057890:Epigenomics / Q000379:methods; D016678:Genome; D023281:Genomics / Q000379:methods* / Q000592:standards; D059014:High-Throughput Nucleotide Sequencing; D006657:Histones / Q000378:metabolism; D006801:Humans; D011485:Protein Binding; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D006657:Histones; D014157:Transcription Factors
keywords: Discrete optimization; Genomics assays; Submodularity