QTL Mapping in the Evolutionary Context

J.C.P. Prins

Abstract

QTL Mapping in the Evolutionary Context Pjotr Prins Laboratory of Nematology, Wageningen University and the Groningen Bioinformatics Cente, The Netherlands QTL mapping, both with genome-wide association studies (GWAS) and linkage studies in experimental populations, is a proven statistical method for disentangling complex traits. Especially now, with the deluge of data and information generated by, for example, RNA-seq, a well designed QTL experiment promises a chance of gaining enough statistical power to say something about multi-gene regulation and interaction. Here we discuss elucidating host-pathogen protein-protein interactions through linkage studies, where evidence of positive selection pressure acts as a prior to QTL analysis.

Original language	English
Publication status	Published - 2011
Event	Zurich Colloquium for Computational Molecular Evolution (2011) - Duration: 23 Nov 2011 → …

Conference/symposium

Conference/symposium	Zurich Colloquium for Computational Molecular Evolution (2011)
Period	23/11/11 → …

Development and application of high throughput computational methods for the identification of biologically significant genome-wide variation in host-microbe interactions
Prins, P. (PhD candidate), Bakker, J. (Promotor) & Smant, G. (Co-promotor)
1/10/07 → 5/10/15
Project: PhD

Cite this

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title = "QTL Mapping in the Evolutionary Context",

abstract = "QTL Mapping in the Evolutionary Context Pjotr Prins Laboratory of Nematology, Wageningen University and the Groningen Bioinformatics Cente, The Netherlands QTL mapping, both with genome-wide association studies (GWAS) and linkage studies in experimental populations, is a proven statistical method for disentangling complex traits. Especially now, with the deluge of data and information generated by, for example, RNA-seq, a well designed QTL experiment promises a chance of gaining enough statistical power to say something about multi-gene regulation and interaction. Here we discuss elucidating host-pathogen protein-protein interactions through linkage studies, where evidence of positive selection pressure acts as a prior to QTL analysis.",

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T1 - QTL Mapping in the Evolutionary Context

AU - Prins, J.C.P.

PY - 2011

Y1 - 2011

N2 - QTL Mapping in the Evolutionary Context Pjotr Prins Laboratory of Nematology, Wageningen University and the Groningen Bioinformatics Cente, The Netherlands QTL mapping, both with genome-wide association studies (GWAS) and linkage studies in experimental populations, is a proven statistical method for disentangling complex traits. Especially now, with the deluge of data and information generated by, for example, RNA-seq, a well designed QTL experiment promises a chance of gaining enough statistical power to say something about multi-gene regulation and interaction. Here we discuss elucidating host-pathogen protein-protein interactions through linkage studies, where evidence of positive selection pressure acts as a prior to QTL analysis.

AB - QTL Mapping in the Evolutionary Context Pjotr Prins Laboratory of Nematology, Wageningen University and the Groningen Bioinformatics Cente, The Netherlands QTL mapping, both with genome-wide association studies (GWAS) and linkage studies in experimental populations, is a proven statistical method for disentangling complex traits. Especially now, with the deluge of data and information generated by, for example, RNA-seq, a well designed QTL experiment promises a chance of gaining enough statistical power to say something about multi-gene regulation and interaction. Here we discuss elucidating host-pathogen protein-protein interactions through linkage studies, where evidence of positive selection pressure acts as a prior to QTL analysis.

M3 - Abstract

T2 - Zurich Colloquium for Computational Molecular Evolution (2011)

Y2 - 23 November 2011

ER -

QTL Mapping in the Evolutionary Context

Abstract

Conference/symposium

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Projects

Development and application of high throughput computational methods for the identification of biologically significant genome-wide variation in host-microbe interactions

Cite this