Evidence map›Paper›PMID 35641766›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Population Structure and Relatedness for Genome-Wide Association Studies.

Sidiki Malle

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Sidiki MalleAssistant professor at Institut Polytechnique Rural de Formation et de Recherche Appliquée (IPR/IFRA) de Katibougou, Koulikoro, Mali. sirikimalle@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The estimation of the population structure and genetic relatedness between individuals within a collection of accessions is important in the formation of core collections for the conservation of genetic resources, uncovering the demographic history of the population under study, as well as for association studies. With the recent development of high-throughput genotyping technologies, several algorithms and methods have been developed and implemented in software to estimate the extent of genetic diversity between individuals. In this chapter, our objective is to describe methods to capture population structure and relatedness in a step-by-step fashion. To exemplify the process, two pruned datasets (14K and 243K SNP markers) were used to investigate population structure and relatedness among a soybean GWAS panel using different approaches and methods.

Indexed as

Genetic Association StudiesGenetics, PopulationGlycine maxPolymorphism, Single NucleotideSoftwareKinshipPopulation structurePrincipal component analysisSNP markers

Identifiers

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.