CLC number: Q348
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2010-05-17
Cited: 1
Clicked: 5433
Wen-jun Zheng, Jian Yang, Jun Zhu. QTLNetworkR: an interactive R package for QTL visualization[J]. Journal of Zhejiang University Science B, 2010, 11(7): 512-515.
@article{title="QTLNetworkR: an interactive R package for QTL visualization",
author="Wen-jun Zheng, Jian Yang, Jun Zhu",
journal="Journal of Zhejiang University Science B",
volume="11",
number="7",
pages="512-515",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B0900384"
}
%0 Journal Article
%T QTLNetworkR: an interactive R package for QTL visualization
%A Wen-jun Zheng
%A Jian Yang
%A Jun Zhu
%J Journal of Zhejiang University SCIENCE B
%V 11
%N 7
%P 512-515
%@ 1673-1581
%D 2010
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B0900384
TY - JOUR
T1 - QTLNetworkR: an interactive R package for QTL visualization
A1 - Wen-jun Zheng
A1 - Jian Yang
A1 - Jun Zhu
J0 - Journal of Zhejiang University Science B
VL - 11
IS - 7
SP - 512
EP - 515
%@ 1673-1581
Y1 - 2010
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B0900384
Abstract: QTLNetworkR is an r package that aims to provide a user-friendly and platform-independent tool to visualize quantitative trait loci (QTL) mapping results. The graphical functions of the QTLNetworkR are based upon lattice and grid packages, and the graphical user interface (GUI) of the QTLNetworkR is built upon RGtk2 and gWidgetsRGtk2 packages. Six functions are designed to help visualize marker interval, putative QTL, QTL-by-environment interactions, marker interval interactions, epistasis, and the predicted genetic architecture of complex traits. It is especially helpful in profiling results for multiple traits at multiple environments. The current version of QTLNetworkR is able to accept QTL mapping results from QTLNetwork, and it is ready for possible extensions to import results from some other QTL mapping software packages. In addition, we presented a QTL mapping result in rice (Oryza sativa) as an example to describe the features of QTLNetworkR.
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