Evidence map›Paper›PMID 16451663›Full record

ArticleBMC genetics2005

Whole-genome association analysis to identify markers associated with recombination rates using single-nucleotide polymorphisms and microsatellites.

Song Huang, Shuang Wang, Nianjun Liu, Liang Chen, Cheongeun Oh, Hongyu Zhao

Open access · diamondAbstract read
In one paragraph

Article in BMC genetics, 2005. 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
0.1field-weighted citation impact, top 51% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

6 authors at 2 institutions in 1 country.

Song HuangProgram of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA. song.huang@yale.edu
Shuang Wang
Nianjun Liu
Liang Chen
Cheongeun Oh
Hongyu Zhao
Yale University · USColumbia University · US

Funding

STATISTICAL METHODS TO MAP GENES FOR COMPLEX TRAITSR01GM059507 · NIGMS · YALE UNIVERSITY · PI ZHAO, HONGYU · 1999 to 2013
$3.6M
NIGMS NIH HHS R01 GM059507NIGMS NIH HHS R01 GM59507
6 · The paper itself

Abstract

Recombination during meiosis is one of the most important biological processes, and the level of recombination rates for a given individual is under genetic control. In this study, we conducted genome-wide association studies to identify chromosomal regions associated with recombination rates. We analyzed genotype data collected on the pedigrees in the Collaborative Study on the Genetics on Alcoholism data provided by Genetic Analysis Workshop 14. A total of 315 microsatellites and 10,081 single-nucleotide polymorphisms from Affymetrix on 22 autosomal chromosomes were used in our association analysis. Genome-wide gender-specific recombination counts for family founders were inferred first and association analysis was performed using multiple linear regressions. We used the positive false discovery rate (pFDR) to account for multiple comparisons in the two genome-wide scans. Eight regions showed some evidence of association with recombination counts based on the single-nucleotide polymorphism analysis after adjusting for multiple comparisons. However, no region was found to be significant using microsatellites.

Indexed as

Genome-Wide Association StudyFemaleGenetic MarkersHumansMaleMicrosatellite RepeatsPolymorphism, Single NucleotideRecombination, GeneticSex CharacteristicsGenetic Markers

Identifiers

PMID16451663
PMCPMC1866732
OpenAlexW2017521441

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.