Evidence map›Paper›PMID 39336765›Full record

ArticleGenes2024

A New Method for Conditional Gene-Based Analysis Effectively Accounts for the Regional Polygenic Background.

Gulnara R Svishcheva, Nadezhda M Belonogova, Anatoly V Kirichenko, Yakov A Tsepilov, Tatiana I Axenovich

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Gulnara R SvishchevaInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Ave. Lavrentiev, 10, 630090 Novosibirsk, Russia.ORCID 0000-0001-9478-267X
Nadezhda M BelonogovaInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Ave. Lavrentiev, 10, 630090 Novosibirsk, Russia.
Anatoly V KirichenkoInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Ave. Lavrentiev, 10, 630090 Novosibirsk, Russia.ORCID 0000-0002-9972-9517
Yakov A TsepilovInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Ave. Lavrentiev, 10, 630090 Novosibirsk, Russia.
Tatiana I AxenovichInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Ave. Lavrentiev, 10, 630090 Novosibirsk, Russia.

Funding

Russian Science Foundation 23-25-00209
6 · The paper itself

Abstract

Gene-based association analysis is a powerful tool for identifying genes that explain trait variability. An essential step of this analysis is a conditional analysis. It aims to eliminate the influence of SNPs outside the gene, which are in linkage disequilibrium with intragenic SNPs. The popular conditional analysis method, GCTA-COJO, accounts for the influence of several top independently associated SNPs outside the gene, correcting the z statistics for intragenic SNPs. We suggest a new TauCOR method for conditional gene-based analysis using summary statistics. This method accounts the influence of the full regional polygenic background, correcting the genotype correlations between intragenic SNPs. As a result, the distribution of z statistics for intragenic SNPs becomes conditionally independent of distribution for extragenic SNPs. TauCOR is compatible with any gene-based association test. TauCOR was tested on summary statistics simulated under different scenarios and on real summary statistics for a 'gold standard' gene list from the Open Targets Genetics project. TauCOR proved to be effective in all modelling scenarios and on real data. The TauCOR's strategy showed comparable sensitivity and higher specificity and accuracy than GCTA-COJO on both simulated and real data. The method can be successfully used to improve the effectiveness of gene-based association analyses.

Indexed as

Linkage DisequilibriumMultifactorial InheritancePolymorphism, Single NucleotideGenome-Wide Association StudyGenotypeHumansModels, Geneticconditional distributiongene-based association analysisrandom-effects modelsummary statistics

Identifiers

PMID39336765
PMCPMC11431718

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.