Evidence map›Paper›PMID 36402991›Full record

ArticleBMC bioinformatics2022

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

Xuewen Wang, Bruce Budowle, Jianye Ge

Abstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xuewen WangCenter for Human Identification, Health Science Center, University of North Texas, Fort Worth, TX, USA. xuewen.wang@unthsc.edu.ORCID http://orcid.org/0000-0003-2820-9255
Bruce BudowleCenter for Human Identification, Health Science Center, University of North Texas, Fort Worth, TX, USA.
Jianye GeCenter for Human Identification, Health Science Center, University of North Texas, Fort Worth, TX, USA.

Funding

Office of Justice Programs 15PNIJ-21-GG-04159-RESS
6 · The paper itself

Abstract

backgroundTandem 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.

resultsIn 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.

conclusionUSAT is a user-friendly bioinformatics software for interpretation, visualization, and comparisons of TRs.

Indexed as

Computational BiologyMicrosatellite RepeatsAllelesHaplotypesHumansSequence Analysis, DNAAllele comparisonDNAForensics STRGenome comparisonHaplotypeTandem repeat

Identifiers

PMID36402991
PMCPMC9675219

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.