Evidence map›Paper›PMID 36274121›Full record

ArticleBMC bioinformatics2022

PolyHaplotyper: haplotyping in polyploids based on bi-allelic marker dosage data.

Roeland E Voorrips, Giorgio Tumino

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

2 authors at 2 institutions in 1 country.

Roeland E VoorripsWageningen University and Research - Plant Breeding, Wageningen, The Netherlands. roeland.voorrips@wur.nl.ORCID http://orcid.org/0000-0003-4388-9244
Giorgio TuminoWageningen University and Research - Plant Breeding, Wageningen, The Netherlands.
Graduate School Experimental Plant Sciences · NLWageningen University & Research · NL

Funding

Ministry of Agriculture, Nature and Food Quality of the Netherlands BO-50-002-022Ministry of Agriculture, Nature and Food Quality of the Netherlands LWV20.112
6 · The paper itself

Abstract

backgroundFor genetic analyses, multi-allelic markers have an advantage over bi-allelic markers like SNPs (single nucleotide polymorphisms) in that they carry more information about the genetic constitution of individuals. This is especially the case in polyploids, where individuals carry more than two alleles at each locus. Haploblocks are multi-allelic markers that can be derived by phasing sets of closely-linked SNP markers. Phased haploblocks, similarly to other multi-allelic markers, will therefore be advantageous in genetic tasks like linkage mapping, QTL mapping and genome-wide association studies.

resultsWe present a new method to reconstruct haplotypes from SNP dosages derived from genotyping arrays, which is applicable to polyploids. This method is implemented in the software package PolyHaplotyper. In contrast to existing packages for polyploids it makes use of full-sib families among the samples to guide the haplotyping process. We show that in this situation it is much more accurate than other available software, using experimental hexaploid data and simulated tetraploid data.

conclusionsOur method and the software package PolyHaplotyper in which it is implemented extend the available tools for haplotyping in polyploids. They perform especially well in situations where one or more full-sib families are present.

Indexed as

Genome-Wide Association StudyPolyploidyAllelesChromosome MappingHaplotypesHumansHaplotypeMulti-allelic markerPolyploidSNP array

Identifiers

PMID36274121
PMCPMC9590153
OpenAlexW4307106782

What OpenQuestion 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 OpenQuestion graph.