Evidence map›Paper›PMID 24353318›Full record

ArticleNucleic acids research2014

Inferring short tandem repeat variation from paired-end short reads.

Minh Duc Cao, Edward Tasker, Kai Willadsen, Michael Imelfort, Sailaja Vishwanathan, Sridevi Sureshkumar, Sureshkumar Balasubramanian, Mikael Bodén

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

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  8. The Concept of Immunogenetics.Advances in experimental medicine and biology · 2022
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  18. Characterization of Duck (Frontiers in genetics · 2018
    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

8 authors.

Minh Duc CaoSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, St Lucia QLD 4072, Australia, Clayton School of Information Technology, Monash University, Clayton, VIC 3800, Australia, School of Biological Sciences, Monash University, Melbourne, Australia and Advanced Water Management Centre, The University of Queensland, Queensland, Australia.
Edward Tasker
Kai Willadsen
Michael Imelfort
Sailaja Vishwanathan
Sridevi Sureshkumar
Sureshkumar Balasubramanian
Mikael Bodén

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advances of high-throughput sequencing offer an unprecedented opportunity to study genetic variation. This is challenged by the difficulty of resolving variant calls in repetitive DNA regions. We present a Bayesian method to estimate repeat-length variation from paired-end sequence read data. The method makes variant calls based on deviations in sequence fragment sizes, allowing the analysis of repeats at lengths of relevance to a range of phenotypes. We demonstrate the method's ability to detect and quantify changes in repeat lengths from short read genomic sequence data across genotypes. We use the method to estimate repeat variation among 12 strains of Arabidopsis thaliana and demonstrate experimentally that our method compares favourably against existing methods. Using this method, we have identified all repeats across the genome, which are likely to be polymorphic. In addition, our predicted polymorphic repeats also included the only known repeat expansion in A. thaliana, suggesting an ability to discover potential unstable repeats.

Indexed as

Genetic VariationTandem Repeat SequencesArabidopsisBayes TheoremHigh-Throughput Nucleotide SequencingSequence Analysis, DNASoftware

Identifiers

PMID24353318
PMCPMC3919575

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.