ArticleBioinformatics (Oxford, England)2017
GLANET: genomic loci annotation and enrichment tool.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Demystifying non-coding GWAS variants: an overview of computational tools and methods.Human molecular genetics · 2022Review
- Novel open reading frames in human accelerated regions and transposable elements reveal new leads to understand schizophrenia and bipolar disorder.Molecular psychiatry · 2022Article
- NoRCE: non-coding RNA sets cis enrichment tool.BMC bioinformatics · 2021Article
- Analytical Approaches for ATAC-seq Data Analysis.Current protocols in human genetics · 2020Article
- Non-canonical RNA-DNA differences and other human genomic features are enriched within very short tandem repeats.PLoS computational biology · 2020Article
- AnnoGen: annotating genome-wide pragmatic features.Bioinformatics (Oxford, England) · 2020Article
- JOA: Joint Overlap Analysis of multiple genomic interval sets.BMC bioinformatics · 2019Article
- Coloc-stats: a unified web interface to perform colocalization analysis of genomic features.Nucleic acids research · 2018Article
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Authors and funding
4 authors.
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Abstract
motivationGenomic studies identify genomic loci representing genetic variations, transcription factor (TF) occupancy, or histone modification through next generation sequencing (NGS) technologies. Interpreting these loci requires evaluating them with known genomic and epigenomic annotations.
resultsWe present GLANET as a comprehensive annotation and enrichment analysis tool which implements a sampling-based enrichment test that accounts for GC content and/or mappability biases, jointly or separately. GLANET annotates and performs enrichment analysis on these loci with a rich library. We introduce and perform novel data-driven computational experiments for assessing the power and Type-I error of its enrichment procedure which show that GLANET has attained high statistical power and well-controlled Type-I error rate. As a key feature, users can easily extend its library with new gene sets and genomic intervals. Other key features include assessment of impact of single nucleotide variants (SNPs) on TF binding sites and regulation based pathway enrichment analysis. AVAILABILITY AND IMPLEMENTATION: GLANET can be run using its GUI or on command line. GLANET's source code is available at https://github.com/burcakotlu/GLANET . Tutorials are provided at https://glanet.readthedocs.org . CONTACT: burcak@ceng.metu.edu.tr or oznur.tastan@cs.bilkent.edu.tr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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