Evidence map›Paper›PMID 31269027›Full record

ArticlePLoS genetics2019

scoreInvHap: Inversion genotyping for genome-wide association studies.

Carlos Ruiz-Arenas, Alejandro Cáceres, Marcos López-Sánchez, Ignacio Tolosana, Luis Pérez-Jurado, Juan R González

Abstract read
In one paragraph

Article in PLoS genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Genomic architecture and functional effects of potential human inversion supergenes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Review
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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

6 authors.

Carlos Ruiz-ArenasISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.ORCID 0000-0002-6014-3498
Alejandro CáceresISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.ORCID 0000-0001-8551-6695
Marcos López-SánchezGenetics Unit, Universitat Pompeu Fabra, Barcelona, Spain.ORCID 0000-0002-1517-5968
Ignacio TolosanaISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.ORCID 0000-0002-3766-8296
Luis Pérez-JuradoGenetics Unit, Universitat Pompeu Fabra, Barcelona, Spain.
Juan R GonzálezISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.ORCID 0000-0003-3267-2146

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymorphic inversions contribute to adaptation and phenotypic variation. However, large multi-centric association studies of inversions remain challenging. We present scoreInvHap, a method to genotype inversions from SNP data for genome-wide association studies (GWASs), overcoming important limitations of current methods and outperforming them in accuracy and applicability. scoreInvHap calls individual inversion-genotypes from a similarity score to the SNPs of experimentally validated references. It can be used on different sources of SNP data, including those with low SNP coverage such as exome sequencing, and is easily adaptable to genotype new inversions, either in humans or in other species. We present 20 human inversions that can be reliably and easily genotyped with scoreInvHap to discover their role in complex human traits, and illustrate a first genome-wide association study of experimentally-validated human inversions. scoreInvHap is implemented in R and it is freely available from Bioconductor.

Indexed as

Sequence InversionGenome-Wide Association StudyGenotyping TechniquesHumansPolymorphism, Single NucleotideSoftware

Identifiers

PMID31269027
PMCPMC6608898

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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.