Journal of Zhejiang University SCIENCE B

, Volume 11, Issue 7, pp 512–515 | Cite as

QTLNetworkR: an interactive R package for QTL visualization

  • Wen-jun Zheng
  • Jian Yang
  • Jun Zhu
Brief Communications


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.

Key words

Visualization Quantitative trait loci (QTL) QTL mapping R package QTLNetworkR 

CLC number



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  1. Broman, K.W., Wu, H., Sen, S., Churchill, G.A., 2003. R/qtl: QTL mapping in experimental crosses. Bioinformatics, 19(7):889–890. [doi:10.1093/bioinformatics/btg112]CrossRefPubMedGoogle Scholar
  2. Clark, R.M., Wagler, T.N., Quijada, P., Doebley, J., 2006. A distant upstream enhancer at the maize domestication gene tb1 has pleiotropic effects on plant and inflorescent architecture. Nature Genetics, 38(5):594–597. [doi:10. 1038/ng1784]CrossRefPubMedGoogle Scholar
  3. Doebley, J., 2004. The genetics of maize evolution. Annual Review of Genetics, 38(1):37–59. [doi:10.1146/annurev.genet.38.072902.092425]CrossRefPubMedGoogle Scholar
  4. Haley, C.S., Knott, S.A., 1992. A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity, 69(4):315–324.PubMedGoogle Scholar
  5. Ihaka, R., Gentleman, R., 1996. R: a language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3):299–314. [doi:10.2307/1390807]CrossRefGoogle Scholar
  6. Joehanes, R., Nelson, J.C., 2008. QGene 4.0, an extensible Java QTL-analysis platform. Bioinformatics, 24(23): 2788–2789. [doi:10.1093/bioinformatics/btn523]CrossRefPubMedGoogle Scholar
  7. Jourjon, M.F., Jasson, S., Marcel, J., Ngom, B., Mangin, B., 2005. MCQTL: multi-allelic QTL mapping in multi-cross design. Bioinformatics, 21(1):128–130. [doi:10.1093/bioinformatics/bth481]CrossRefPubMedGoogle Scholar
  8. Kao, C.H., Zeng, Z.B., Teasdale, R.D., 1999. Multiple interval mapping for quantitative trait loci. Genetics, 152(3): 1203–1216.PubMedGoogle Scholar
  9. Lander, E.S., Botstein, D., 1989. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 121(1):185–199.PubMedGoogle Scholar
  10. Lander, E.S., Green, P., Abrahamson, J., Barlow, A., Daly, M.J., Lincoln, S.E., Newberg, L.A., 1987. MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics, 1(2):174–181. [doi:10.1016/0888-7543(87)90010-3]CrossRefPubMedGoogle Scholar
  11. Mackay, T.F., 2001. The genetic architecture of quantitative traits. Annual Review of Genetics, 35(1):303–339. [doi:10.1146/annurev.genet.35.102401.090633]CrossRefPubMedGoogle Scholar
  12. Manly, K.F., Cudmore, R.H.Jr., Meer, J.M., 2001. Map Manager QTX, cross-platform software for genetic mapping. Mammalian Genome, 12(12):930–932. [doi:10.1007/s00335-001-1016-3]CrossRefPubMedGoogle Scholar
  13. Seaton, G., Haley, C.S., Knott, S.A., Kearsey, M., Visscher, P.M., 2002. QTL Express: mapping quantitative trait loci in simple and complex pedigrees. Bioinformatics, 18(2): 339–340. [doi:10.1093/bioinformatics/18.2.339]CrossRefPubMedGoogle Scholar
  14. Wang, D.L., Zhu, J., Li, Z.K., Paterson, A.H., 1999. Mapping QTLs with epistatic effects and QTL×environment interactions by mixed linear model approaches. Theoretical and Applied Genetics, 99(7–8):1255–1264. [doi:10.1007/s001220051331]CrossRefGoogle Scholar
  15. Wang, S.C., Basten, C.J., Zeng, Z.B., 2006. Windows QTL Cartographer 2.5. Available from
  16. Wright, S., 1980. Genic and organismic selection. Evolution, 34(5):825–843. [doi:10.2307/2407990]CrossRefGoogle Scholar
  17. Yang, J., Zhu, J., Williams, R.W., 2007. Mapping the genetic architecture of complex traits in experimental populations. Bioinformatics, 23(12):1527–1536. [doi:10.1093/bioinformatics/btm143]CrossRefPubMedGoogle Scholar
  18. Yang, J., Hu, C., Hu, H., Yu, R., Xia, Z., Ye, X., Zhu, J., 2008. QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics, 24(5):721–723. [doi:10.1093/bioinformatics/btm494]CrossRefPubMedGoogle Scholar
  19. Zeng, Z.B., 1994. Precision mapping of quantitative trait loci. Genetics, 136(4):1457–1468.PubMedGoogle Scholar

Copyright information

© Zhejiang University and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Institute of BioinformaticsZhejiang UniversityHangzhouChina
  2. 2.Queensland Institute of Medical ResearchBrisbaneAustralia

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