Evidence map›Paper›PMID 41028371›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Local Haplotyping Analysis for Flowering Time in Soybean Using Crosshap.

Shameela Mohamedikbal, Shriprabha R Upadhyaya, Mitchell Bestry, Jacob I Marsh, David Edwards

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Article in Methods in molecular biology (Clifton, N.J.), 2026. 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
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Shameela MohamedikbalCentre for Applied Bioinformatics, University of Western Australia, Perth, WA, Australia.
Shriprabha R UpadhyayaCentre for Applied Bioinformatics, University of Western Australia, Perth, WA, Australia.
Mitchell BestryCentre for Applied Bioinformatics, University of Western Australia, Perth, WA, Australia.
Jacob I MarshDepartment of Biology, University of North Carolina, Chapel Hill, NC, USA.
David EdwardsCentre for Applied Bioinformatics, University of Western Australia, Perth, WA, Australia. dave.edwards@uwa.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The vast amount of genomic data available for various plant species has enabled a greater understanding of genomic regions associated with phenotypic variation, mainly through approaches such as Genome-Wide Association Studies (GWAS). However, relying solely on GWAS results limits our understanding of trait variation, as it focuses on individual SNPs without considering the linked variants that may also influence the trait. As a follow-up to GWAS, haplotype analysis focusing on local regions of the genome can provide detailed insights into the genetic variants associated with a trait. crosshap, a local haplotyping R-package, identifies and visualises haplotype structures, allowing users to explore allelic diversity and associated phenotypic variation in targeted genomic regions. This chapter demonstrates local haplotyping analysis using crosshap to understand the genetic control of flowering time in domesticated and wild soybean, informing breeding strategies and crop improvement efforts; however, crosshap can be applied to any species where suitable data is available.

Indexed as

FlowersGlycine maxHaplotypesSoftwareGenome, PlantGenome-Wide Association StudyPhenotypePlant BreedingPolymorphism, Single NucleotideQuantitative Trait LociBioinformaticsCrosshapFlowering timeHaplotypesLocal haplotypingRSoybean

Identifiers

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Registered trials

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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.