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Do Molecular Markers Inform About Pleiotropy?

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Do Molecular Markers Inform About Pleiotropy? / Gianola, Daniel; de los Campos, Gustavo; Toro, Miguel A et al.

In: Genetics, Vol. 201, No. 1, 01.09.2015, p. 23-29.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Gianola, D, de los Campos, G, Toro, MA, Naya, H, Schön, C-C & Sorensen, D 2015, 'Do Molecular Markers Inform About Pleiotropy?', Genetics, vol. 201, no. 1, pp. 23-29. https://doi.org/10.1534/genetics.115.179978

APA

Gianola, D., de los Campos, G., Toro, M. A., Naya, H., Schön, C-C., & Sorensen, D. (2015). Do Molecular Markers Inform About Pleiotropy? Genetics, 201(1), 23-29. https://doi.org/10.1534/genetics.115.179978

CBE

Gianola D, de los Campos G, Toro MA, Naya H, Schön C-C, Sorensen D. 2015. Do Molecular Markers Inform About Pleiotropy?. Genetics. 201(1):23-29. https://doi.org/10.1534/genetics.115.179978

MLA

Vancouver

Gianola D, de los Campos G, Toro MA, Naya H, Schön C-C, Sorensen D. Do Molecular Markers Inform About Pleiotropy? Genetics. 2015 Sep 1;201(1):23-29. https://doi.org/10.1534/genetics.115.179978

Author

Gianola, Daniel ; de los Campos, Gustavo ; Toro, Miguel A et al. / Do Molecular Markers Inform About Pleiotropy?. In: Genetics. 2015 ; Vol. 201, No. 1. pp. 23-29.

Bibtex

@article{5651cd1eb27c487a9228c179b829f124,
title = "Do Molecular Markers Inform About Pleiotropy?",
abstract = "The availability of dense panels of common single nucleotide polymorphisms and of sequence variants has facilitated the study of statistical features of the genetic architecture of complex traits and diseases via whole-genome regressions (WGR). At the onset, traits were analyzed trait by trait but recently WGR have been extended for analysis of several traits jointly. The expectation is that such an approach would offer insight into mechanisms that cause trait associations, such as pleiotropy. We demonstrate that correlation parameters inferred using markers can give a distorted picture of the genetic correlation between traits. In the absence of knowledge of linkage disequilibrium relationships between quantitative or disease trait loci and markers, speculating about genetic correlation and its causes (such as pleiotropy) using genomic data is conjectural.",
author = "Daniel Gianola and {de los Campos}, Gustavo and Toro, {Miguel A} and Hugo Naya and Chris-Carolin Sch{\"o}n and Daniel Sorensen",
note = "Copyright {\textcopyright} 2015, The Genetics Society of America.",
year = "2015",
month = sep,
day = "1",
doi = "10.1534/genetics.115.179978",
language = "English",
volume = "201",
pages = "23--29",
journal = "Genetics",
issn = "1943-2631",
publisher = "The Genetics Society of America (GSA)",
number = "1",

}

RIS

TY - JOUR

T1 - Do Molecular Markers Inform About Pleiotropy?

AU - Gianola, Daniel

AU - de los Campos, Gustavo

AU - Toro, Miguel A

AU - Naya, Hugo

AU - Schön, Chris-Carolin

AU - Sorensen, Daniel

N1 - Copyright © 2015, The Genetics Society of America.

PY - 2015/9/1

Y1 - 2015/9/1

N2 - The availability of dense panels of common single nucleotide polymorphisms and of sequence variants has facilitated the study of statistical features of the genetic architecture of complex traits and diseases via whole-genome regressions (WGR). At the onset, traits were analyzed trait by trait but recently WGR have been extended for analysis of several traits jointly. The expectation is that such an approach would offer insight into mechanisms that cause trait associations, such as pleiotropy. We demonstrate that correlation parameters inferred using markers can give a distorted picture of the genetic correlation between traits. In the absence of knowledge of linkage disequilibrium relationships between quantitative or disease trait loci and markers, speculating about genetic correlation and its causes (such as pleiotropy) using genomic data is conjectural.

AB - The availability of dense panels of common single nucleotide polymorphisms and of sequence variants has facilitated the study of statistical features of the genetic architecture of complex traits and diseases via whole-genome regressions (WGR). At the onset, traits were analyzed trait by trait but recently WGR have been extended for analysis of several traits jointly. The expectation is that such an approach would offer insight into mechanisms that cause trait associations, such as pleiotropy. We demonstrate that correlation parameters inferred using markers can give a distorted picture of the genetic correlation between traits. In the absence of knowledge of linkage disequilibrium relationships between quantitative or disease trait loci and markers, speculating about genetic correlation and its causes (such as pleiotropy) using genomic data is conjectural.

U2 - 10.1534/genetics.115.179978

DO - 10.1534/genetics.115.179978

M3 - Journal article

C2 - 26205989

VL - 201

SP - 23

EP - 29

JO - Genetics

JF - Genetics

SN - 1943-2631

IS - 1

ER -