Evidence map›Paper›PMID 31890145›Full record

ArticleComputational and structural biotechnology journal2020

QTL.gCIMapping.GUI v2.0: An R software for detecting small-effect and linked QTLs for quantitative traits in bi-parental segregation populations.

Ya-Wen Zhang, Yang-Jun Wen, Jim M Dunwell, Yuan-Ming Zhang

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  10. Dissection of theFrontiers in plant science · 2024
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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

4 authors.

Ya-Wen ZhangCrop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
Yang-Jun WenState Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
Jim M DunwellSchool of Agriculture, Policy and Development, University of Reading, Reading RG6 6AR, United Kingdom.
Yuan-Ming ZhangCrop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The methodologies and software packages for mapping quantitative trait loci (QTLs) in bi-parental segregation populations are well established. However, it is still difficult to detect small-effect and linked QTLs. To address this issue, we proposed a genome-wide composite interval mapping (GCIM) in bi-parental segregation populations. To popularize this method, we developed an R package. This program with two versions (Graphical User Interface: QTL.gCIMapping.GUI v2.0 and code: QTL.gCIMapping v3.2) can be used to identify QTLs for quantitative traits in recombinant inbred lines, doubled haploid lines, backcross and F

Indexed as

GCIMLinked QTLQTL.gCIMappingQTL.gCIMapping.GUIRSmall-effect QTL

Identifiers

PMID31890145
PMCPMC6921137

What OpenQuestion holds

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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.