Dataset Information

GLANET: genomic loci annotation and enrichment tool.

ABSTRACT: Motivation:Genomic 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. Results:We 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.

SUBMITTER: Otlu B

PROVIDER: S-EPMC6355098 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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GLANET: genomic loci annotation and enrichment tool.

Otlu Burçak B Firtina Can C Keles Sündüz S Tastan Oznur O

Bioinformatics (Oxford, England) 20170901 18

<h4>Motivation</h4>Genomic 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.<h4>Results</h4>We 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, ...[more]

PMID: 28541490

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Project description:BackgroundWhole genome sequencing is effective at identification of small variants, but because it is based on short reads, assessment of structural variants (SVs) is limited. The advent of Optical Genome Mapping (OGM), which utilizes long fluorescently labeled DNA molecules for de novo genome assembly and SV calling, has allowed for increased sensitivity and specificity in SV detection. However, compared to small variant annotation tools, OGM-based SV annotation software has seen little development, and currently available SV annotation tools do not provide sufficient information for determination of variant pathogenicity.ResultsWe developed an R-based package, nanotatoR, which provides comprehensive annotation as a tool for SV classification. nanotatoR uses both external (DGV; DECIPHER; Bionano Genomics BNDB) and internal (user-defined) databases to estimate SV frequency. Human genome reference GRCh37/38-based BED files are used to annotate SVs with overlapping, upstream, and downstream genes. Overlap percentages and distances for nearest genes are calculated and can be used for filtration. A primary gene list is extracted from public databases based on the patient's phenotype and used to filter genes overlapping SVs, providing the analyst with an easy way to prioritize variants. If available, expression of overlapping or nearby genes of interest is extracted (e.g. from an RNA-Seq dataset, allowing the user to assess the effects of SVs on the transcriptome). Most quality-control filtration parameters are customizable by the user. The output is given in an Excel file format, subdivided into multiple sheets based on SV type and inheritance pattern (INDELs, inversions, translocations, de novo, etc.). nanotatoR passed all quality and run time criteria of Bioconductor, where it was accepted in the April 2019 release. We evaluated nanotatoR's annotation capabilities using publicly available reference datasets: the singleton sample NA12878, mapped with two types of enzyme labeling, and the NA24143 trio. nanotatoR was also able to accurately filter the known pathogenic variants in a cohort of patients with Duchenne Muscular Dystrophy for which we had previously demonstrated the diagnostic ability of OGM.ConclusionsThe extensive annotation enables users to rapidly identify potential pathogenic SVs, a critical step toward use of OGM in the clinical setting.

Project description:BACKGROUND: There is an ever increasing rate of data made available on genetic variation, transcriptomes and proteomes. Similarly, a growing variety of bioinformatic programs are becoming available from many diverse sources, designed to identify a myriad of sequence patterns considered to have potential biological importance within inter-genic regions, genes, transcripts, and proteins. However, biologists require easy to use, uncomplicated tools to integrate this information, visualise and print gene annotations. Integrating this information usually requires considerable informatics skills, and comprehensive knowledge of the data format to make full use of this information. Tools are needed to explore gene model variants by allowing users the ability to create alternative transcript models using novel combinations of exons not necessarily represented in current database deposits of mRNA/cDNA sequences. RESULTS: Djinn Lite is designed to be an intuitive program for storing and visually exploring of custom annotations relating to a eukaryotic gene sequence and its modelled gene products. In particular, it is helpful in developing hypothesis regarding alternate splicing of transcripts by allowing the construction of model transcripts and inspection of their resulting translations. It facilitates the ability to view a gene and its gene products in one synchronised graphical view, allowing one to drill down into sequence related data. Colour highlighting of selected sequences and added annotations further supports exploration, visualisation of sequence regions and motifs known or predicted to be biologically significant. CONCLUSION: Gene annotating remains an ongoing and challenging task that will continue as gene structures, gene transcription repertoires, disease loci, protein products and their interactions become more precisely defined. Djinn Lite offers an accessible interface to help accumulate, enrich, and individualize sequence annotations relating to a gene, its transcripts and translations. The mechanism of transcript definition and creation, and subsequent navigation and exploration of features, are very intuitive and demand only a short learning curve. Ultimately, Djinn Lite can form the basis for providing valuable clues to plan new experiments, providing storage of sequences and annotations for dedication to customised projects. The application is appropriate for Windows 98-ME-2000-XP-2003 operating systems.

Dataset Information

GLANET: genomic loci annotation and enrichment tool.

Publications

GLANET: genomic loci annotation and enrichment tool.

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