TIVAN-indel

TIVAN-indel annotates and predicts noncoding regulatory small insertions and deletions (sindels) in the human genome to assess their regulatory potential and effects on gene expression.


Key Features:

  • Supervised machine learning: Trains predictive models using labeled nc-sindels identified from cis-expression quantitative trait loci (eQTL) analyses.
  • GTEx training set: Leverages labeled nc-sindels derived from cis-eQTL analyses across 44 tissues in the Genotype-Tissue Expression (GTEx) project.
  • Integration of annotations and epigenomics: Combines generic functional annotations with extensive epigenomic profiles to inform predictions.
  • Tissue-specific predictions: Produces predictions that operate within and across tissue contexts to capture tissue-specific regulatory effects.
  • Independent validation: Validates model performance using data from 15 immune cell types in the Database of Immune Cell Expression study.
  • Enrichment analysis: Performs enrichment analysis of true and predicted sindels in chromatin interactions, open chromatin regions, and histone modification sites.

Scientific Applications:

  • nc-sindel regulatory annotation: Identify and prioritize noncoding sindels with predicted regulatory potential for downstream study.
  • Gene expression impact studies: Investigate how nc-sindels influence gene expression via cis-eQTL–derived labels and epigenomic context.
  • Disease and phenotype investigation: Examine roles of regulatory nc-sindels in disease mechanisms and phenotypic variation.
  • Regulatory region enrichment analysis: Assess overlap and enrichment of true and predicted sindels in chromatin interactions, open chromatin regions, and histone modification sites.

Methodology:

Applies supervised machine learning trained on labeled nc-sindels from cis-eQTL analyses across 44 GTEx tissues, integrates generic functional annotations and epigenomic profiles, validates using 15 immune cell types from the Database of Immune Cell Expression, and conducts enrichment analyses in chromatin interactions, open chromatin regions, and histone modification sites.

Topics

Details

License:
BSD-3-Clause
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Python, R
Added:
3/28/2023
Last Updated:
11/24/2024

Operations

Publications

Agarwal A, Zhao F, Jiang Y, Chen L. TIVAN-indel: a computational framework for annotating and predicting non-coding regulatory small insertions and deletions. Bioinformatics. 2023;39(2). doi:10.1093/bioinformatics/btad060. PMID:36707993. PMCID:PMC9900211.

PMID: 36707993
PMCID: PMC9900211
Funding: - National Institutes of Health: R35GM142701