Evidence map›Paper›PMID 26037133›Full record

ArticleHuman mutation2015

Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data.

Christopher M Watson, Laura A Crinnion, Juliana Gurgel-Gianetti, Sally M Harrison, Catherine Daly, Agne Antanavicuite, Carolina Lascelles, Alexander F Markham, Sergio D J Pena, David T Bonthron and 1 more

Abstract read
In one paragraph

Article in Human mutation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Homozygous NonsenseJournal of clinical medicine · 2026
    Article
  2. A homozygousJBMR plus · 2024
    Article
  3. Mapping the Most Common Founder Variant inJournal of clinical medicine · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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

11 authors.

Christopher M WatsonSchool of Medicine, University of Leeds, Leeds, United Kingdom.
Laura A CrinnionSchool of Medicine, University of Leeds, Leeds, United Kingdom.
Juliana Gurgel-GianettiDepartment of Pediatrics, Faculty of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Sally M HarrisonSchool of Medicine, University of Leeds, Leeds, United Kingdom.
Catherine DalySchool of Medicine, University of Leeds, Leeds, United Kingdom.
Agne AntanavicuiteSchool of Medicine, University of Leeds, Leeds, United Kingdom.
Carolina LascellesSchool of Medicine, University of Leeds, Leeds, United Kingdom.
Alexander F MarkhamSchool of Medicine, University of Leeds, Leeds, United Kingdom.
Sergio D J PenaLaboratory of Clinical Genomics, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
David T BonthronSchool of Medicine, University of Leeds, Leeds, United Kingdom.
Ian M CarrSchool of Medicine, University of Leeds, Leeds, United Kingdom.

Funding

Medical Research Council MR/L01629X/1
6 · The paper itself

Abstract

Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease-causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome-wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution.

Indexed as

Genetic VariationGenotypeHigh-Throughput Nucleotide SequencingPolymorphism, Single NucleotideSoftwareChromosome MappingComputational BiologyConsanguinityExomeGenetic Association StudiesHumansInheritance PatternsPedigreeautozygosity mappingexomenext generation sequencingsoftware

Identifiers

PMID26037133
PMCPMC4744743

What OpenQuestion holds

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Registered trials

None linked

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.