Seten

Seten analyzes condition-specific CLIP-seq profiles to identify and compare biological processes, phenotypes, and diseases associated with RNA-binding proteins (RBPs).

Key Features:

• Integration of peak calling outputs: Accepts BED files generated by various peak calling algorithms that include scores indicating the binding extent of RBPs on target transcripts.
• Functional enrichment and gene set enrichment: Performs traditional functional enrichment and gene set enrichment analysis across gene set collections including BioCarta, KEGG, Reactome, Gene Ontology (GO), Human Phenotype Ontology (HPO), and MalaCards Disease Ontology.
• Comparative analysis and visualization: Enables dynamic comparison of associated gene sets across datasets and represents comparisons using bubble charts.
• Multi-organism support: Supports analysis for fruit fly, human, mouse, rat, worm, and yeast.
• Benchmarking and validation: Was benchmarked using eCLIP data for IGF2BP1, SRSF7, and PTBP1 against CRISPR RNA-seq in K562 cells and randomized negative controls, reporting that its gene set enrichment method outperformed traditional functional enrichment in discovery precision.

Scientific Applications:

• Post-transcriptional regulation analysis: Enables identification of biological processes and regulatory roles of RBPs from CLIP-seq interaction landscapes at single-nucleotide resolution.
• Disease and phenotype association: Facilitates linking RBPs to phenotypes and diseases via enrichment against HPO and MalaCards Disease Ontology.
• Condition-specific comparison of RBP binding: Supports comparative studies of RBP binding patterns across conditions to investigate cellular responses and disease mechanisms.

Methodology:

Accepts BED files with peak scores from peak callers; performs traditional functional enrichment and gene set enrichment across BioCarta, KEGG, Reactome, GO, HPO, and MalaCards; generates comparative bubble-chart visualizations; and was benchmarked using eCLIP data for IGF2BP1, SRSF7, and PTBP1 versus CRISPR RNA-seq in K562 and randomized negative controls.