USAT: a bioinformatic toolkit to facilitate interpretation and comparative visualization of tandem repeat sequences.

Allele comparison DNA Forensics STR Genome comparison Haplotype Tandem repeat

Journal

BMC bioinformatics
ISSN: 1471-2105
Titre abrégé: BMC Bioinformatics
Pays: England
ID NLM: 100965194

Informations de publication

Date de publication:
19 Nov 2022
Historique:
received: 10 05 2022
accepted: 29 10 2022
entrez: 19 11 2022
pubmed: 20 11 2022
medline: 23 11 2022
Statut: epublish

Résumé

Tandem repeats (TR), highly variable genomic variants, are widely used in individual identification, disease diagnostics, and evolutionary studies. The recent advances in sequencing technologies and bioinformatic tools facilitate calling TR haplotypes genome widely. Both length-based and sequence-based TR alleles are used in different applications. However, sequence-based TR alleles could provide the highest precision in characterizing TR haplotypes. The need to identify the differences at the single nucleotide level between or among TR haplotypes with an easy-use bioinformatic tool is essential. In this study, we developed a Universal STR Allele Toolkit (USAT) for TR haplotype analysis, which takes TR haplotype output from existing tools to perform allele size conversion, sequence comparison of haplotypes, figure plotting, comparison for allele distribution, and interactive visualization. An exemplary application of USAT for analysis of the CODIS core STR loci for DNA forensics with benchmarking human individuals demonstrated the capabilities of USAT. USAT has user-friendly graphic interfaces and runs fast in major computing operating systems with parallel computing enabled. USAT is a user-friendly bioinformatics software for interpretation, visualization, and comparisons of TRs.

Sections du résumé

BACKGROUND BACKGROUND
Tandem repeats (TR), highly variable genomic variants, are widely used in individual identification, disease diagnostics, and evolutionary studies. The recent advances in sequencing technologies and bioinformatic tools facilitate calling TR haplotypes genome widely. Both length-based and sequence-based TR alleles are used in different applications. However, sequence-based TR alleles could provide the highest precision in characterizing TR haplotypes. The need to identify the differences at the single nucleotide level between or among TR haplotypes with an easy-use bioinformatic tool is essential.
RESULTS RESULTS
In this study, we developed a Universal STR Allele Toolkit (USAT) for TR haplotype analysis, which takes TR haplotype output from existing tools to perform allele size conversion, sequence comparison of haplotypes, figure plotting, comparison for allele distribution, and interactive visualization. An exemplary application of USAT for analysis of the CODIS core STR loci for DNA forensics with benchmarking human individuals demonstrated the capabilities of USAT. USAT has user-friendly graphic interfaces and runs fast in major computing operating systems with parallel computing enabled.
CONCLUSION CONCLUSIONS
USAT is a user-friendly bioinformatics software for interpretation, visualization, and comparisons of TRs.

Identifiants

pubmed: 36402991
doi: 10.1186/s12859-022-05021-1
pii: 10.1186/s12859-022-05021-1
pmc: PMC9675219
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

497

Subventions

Organisme : Office of Justice Programs
ID : 15PNIJ-21-GG-04159-RESS

Informations de copyright

© 2022. The Author(s).

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Auteurs

Xuewen Wang (X)

Center for Human Identification, Health Science Center, University of North Texas, Fort Worth, TX, USA. xuewen.wang@unthsc.edu.

Bruce Budowle (B)

Center for Human Identification, Health Science Center, University of North Texas, Fort Worth, TX, USA.
Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA.

Jianye Ge (J)

Center for Human Identification, Health Science Center, University of North Texas, Fort Worth, TX, USA.
Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA.

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Classifications MeSH