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Bioinformatics
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GLANET: genomic loci annotation and enrichment tool

Authors: Burçak Otlu; Can Firtina; Sündüz Keles; Öznur Tastan;

GLANET: genomic loci annotation and enrichment tool

Abstract

AbstractMotivationGenomic 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 implementationGLANET 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.Supplementary informationSupplementary data are available at Bioinformatics online.

Country
Turkey
Keywords

Epigenomics, Genome, Human, 005, High-Throughput Nucleotide Sequencing, Molecular Sequence Annotation, DNA, Genomics, Sequence Analysis, DNA, Polymorphism, Single Nucleotide, 306, Genetic Loci, Humans, Software, Protein Binding, Transcription Factors

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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