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The Allele Catalog Tool: a web-based interactive tool for allele discovery and analysis
YO. Chan, N. Dietz, S. Zeng, J. Wang, S. Flint-Garcia, MN. Salazar-Vidal, M. Škrabišová, K. Bilyeu, T. Joshi
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články
NLK
BioMedCentral
od 2000-12-01
BioMedCentral Open Access
od 2000
Directory of Open Access Journals
od 2000
Free Medical Journals
od 2000
PubMed Central
od 2000
ProQuest Central
od 2009-01-01
Open Access Digital Library
od 2000-01-01
Open Access Digital Library
od 2000-07-01
Open Access Digital Library
od 2000-01-01
Medline Complete (EBSCOhost)
od 2000-01-01
Health & Medicine (ProQuest)
od 2009-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2000
Springer Nature OA/Free Journals
od 2000-12-01
- MeSH
- alely * MeSH
- Arabidopsis * genetika MeSH
- data mining * metody MeSH
- datové soubory jako téma * MeSH
- frekvence genu MeSH
- genotyp MeSH
- Glycine max * genetika MeSH
- internet * MeSH
- kukuřice setá * genetika MeSH
- metadata MeSH
- mutace MeSH
- pigmentace genetika MeSH
- rostlinné geny genetika MeSH
- software * MeSH
- substituce aminokyselin MeSH
- vegetační klid genetika MeSH
- vizualizace dat MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: The advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis, and maize. RESULTS: The Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis, and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes. CONCLUSIONS: The Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis, and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website ( https://soykb.org/SoybeanAlleleCatalogTool/ ), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website ( https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana ). Researchers can use this tool to connect variant alleles of genes with meta-information of species.
Christopher S Bond Life Sciences Center University of Missouri Columbia Columbia MO USA
Department of Biochemistry Faculty of Science Palacky University in Olomouc Olomouc Czech Republic
Department of Evolution and Ecology University of California Davis Davis CA USA
Department of Health Management and Informatics University of Missouri Columbia Columbia MO USA
Division of Plant Science and Technology University of Missouri Columbia Columbia MO USA
MU Institute for Data Science and Informatics University of Missouri Columbia Columbia MO USA
Citace poskytuje Crossref.org
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