Evidence map›Paper›PMID 36047334›Full record

ArticleGenetic epidemiology2023

An exploration of linkage fine-mapping on sequences from case-control studies.

Payman Nickchi, Charith Karunarathna, Jinko Graham

Open access · bronzeAbstract read
In one paragraph

Article in Genetic epidemiology, 2023. 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
0.2field-weighted citation impact, top 38% of its field
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 citations in OpenAlex.

  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

3 authors at 2 institutions in 1 country.

Payman NickchiDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Charith KarunarathnaDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Jinko GrahamDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.ORCID 0000-0003-4568-1228
Simon Fraser University · CADalhousie University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Linkage analysis maps genetic loci for a heritable trait by identifying genomic regions with excess relatedness among individuals with similar trait values. Analysis may be conducted on related individuals from families, or on samples of unrelated individuals from a population. For allelically heterogeneous traits, population-based linkage analysis can be more powerful than genotypic-association analysis. Here, we focus on linkage analysis in a population sample, but use sequences rather than individuals as our unit of observation. Earlier investigations of sequence-based linkage mapping relied on known sequence relatedness, whereas we infer relatedness from the sequence data. We propose two ways to associate similarity in relatedness of sequences with similarity in their trait values and compare the resulting linkage methods to two genotypic-association methods. We also introduce a procedure to label case sequences as potential carriers or noncarriers of causal variants after an association has been found. This post hoc labeling of case sequences is based on inferred relatedness to other case sequences. Our simulation results indicate that methods based on sequence relatedness improve localization and perform as well as genotypic-association methods for detecting rare causal variants. Sequence-based linkage analysis therefore has potential to fine-map allelically heterogeneous disease traits.

Indexed as

Models, GeneticQuantitative Trait LociChromosome MappingGenetic LinkageGenotypeHumansLinkage DisequilibriumPhenotypeallelic heterogeneityfine-mappinglinkage analysisrare variantssequence relatedness

Identifiers

PMID36047334
PMCPMC10087369
OpenAlexW4294126403

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.