Seten: a tool for systematic identification and comparison of processes, phenotypes, and diseases associated with RNA-binding proteins from condition-specific CLIP-seq profiles

• DOI: 10.1261/rna.059089.116
• Publication Date: 2017-03-24T00:52:23Z
• Authors: Gungor Budak; Rajneesh Srivastava; Sarath Chandra Janga
• Keywords: KEGG; RNA-Seq

RNA-binding proteins (RBPs) control the regulation of gene expression in eukaryotic genomes at post-transcriptional level by binding to their cognate RNAs. Although several variants CLIP (crosslinking and immunoprecipitation) protocols are currently available study global protein–RNA interaction landscape single-nucleotide resolution a cell, there very few tools that can facilitate understanding dissecting functional associations RBPs from resulting maps. Here, we present Seten, web-based command line tool, which identify compare processes, phenotypes, diseases associated with condition-specific CLIP-seq profiles. Seten uses BED files most peak calling algorithms, include scores reflecting extent an RBP on target transcript, provide both traditional enrichment as well set results for number collections including BioCarta, KEGG, Reactome, Gene Ontology (GO), Human Phenotype (HPO), MalaCards Disease organisms fruit fly, human, mouse, rat, worm, yeast. It also provides option dynamically sets across data bubble charts, comparative analysis. Benchmarking using eCLIP IGF2BP1, SRSF7, PTBP1 against corresponding CRISPR RNA-seq K562 cells randomized negative controls, demonstrated its method outperforms enrichment, significantly contributing discovery true annotations. Comparative performance analysis these revealed higher precision comparable recall observed ChIP-Enrich. Seten's web interface precomputed about 200 interfaces be used analyze sets. We highlight examples show utility rapid profiling various is http://www.iupui.edu/∼sysbio/seten/ .