**iQTL-F2**: R code for mapping imprinted quantitative trait loci (iQTL) in F2 experimental cross.

[R Code for genomewide scan]

[R Code for imprinting test].

**Reference**: Cui, Y.H., Q. Lu, J.M. Cheverud, R.C. Littell and R.L. Wu. (2006) Model for mapping imprinted quantitative trait loci in an inbred F2 design.*Genomics*87: 543-551 [PDF]

**R-GC-test**: R code for testing genetic conflicts (GC) that increase disease risk in human pregnancy with penalized mixture logistic regression.

[R Code for testing genetic conflicts]

**Reference**: Li, S.Y., Q. Lu, W. Fu, R. Romero and Y.H. Cui. (2008) A regularized regression approach for dissecting genetic conflicts that increase disease risk in pregnancy.*Statistical Applications in Genetics and Molecular Biology*[PDF]

**QTL-GPR**: Matlab code for QTL mapping with count trait.

[QTL-GPR.zip]

**Reference**: Cui, Y.H., D.-Y. Kim, and J. Zhu. (2006) On the generalized Poisson regression mixture model for mapping quantitative trait loci with count data.*Genetics*174(4): 2159–2172. [PDF]

**QTL-ZIGP**: R code for QTL mapping with Zero Inflated Generalized Poisson regression model.

[QTL-ZIGP]; [Sample Data]

**Reference**: Cui, Y.H. and W.Z. Yang. (2009) Zero-inflated generalized poisson regression mixture model for mapping quantitative trait loci underlying count trait with many zeros.*Journal of Theoretical Biology*256: 276-285. [PDF];

**iQTL****-VC**: R code for iQTL mapping with Variance Component model in experimental cross.

[iQTL-VC.zip];

**Reference**: Li, G.X. and Y.H. Cui. (2010) A general statistical framework for dissecting parent-of-origin effects underlying triploid endosperm traits in flowering plants.*Annals of Applied Statistics*4(3): 1214-1233. [PDF]|[Link to the Journal].

**HAPAL**: R code for mapping HAPlotype-haplotype interactions with Adaptive Lasso.

[HAPAL.zip];

**Reference**: Li, M., R. Romero, W.J. Fu and Y.H. Cui. (2010) Mapping haplotype-haplotype interactions with adaptive LASSO.*BMC Genetics*11:79 [ PubMed]

**VCGE**: R code for gene-environment interaction with varying coefficient model.

[VCGE.zip];

**Reference**:Ma, S.J., L.J. Yang, R. Romero, and Y.H. Cui. (2011) Varying coefficient model for gene-environment interaction: a non-linear look.*Bioinformatics*27(15): 2119-2126 [PDF]

**SPA3G**: R package for Gene-centric Gene-Gene Interaction.

[SPA3G];

**Reference**: Li SY and YH Cui. (2012) Gene-centric gene-gene interaction: a model-based kernel machine method.*Annals of Applied Statistics*6(3): 1134-1161. [PDF]

**diSNPselection**: Matlab code for disease informative SNP (diSNP) selection for gene-based association tests.

[diSNPselection.zip];

**Reference**: Wu, C and Y. Cui. (2014) Boosting signals in gene-based association studies via efficient SNP selection.*Briefings in Bioinformatics*. 15: 279-291.

**GxE****-selection**: R code for variable selection for gene-environment interactions.

[GxEselection.zip];

**Reference**: Wu, C, P-S. Zhong and Y. Cui. (2015) High-dimensional variable selection for gene-environment interactions. [preprint]

**caPC**: R code for "Learning directed acyclic graphical structures with genetical genomics data".

[caPC.rar];

**Reference**: Gao, B. and Y. Cui. (2015) Learning directed acyclic graphical structures with genetical genomics data.*Bioinformatics*31: 3953-3960.**PLVMICM**: Matlab and C code for "Partial linear varying multi-index coefficient model for integrative gene-environment interactions".

[PLVMICM.rar];

**Reference**: Liu, X., Y. Cui and R. Li. (2016) Partial linear varying multi-index coefficient model for integrative gene-environment interactions.*Statistica**Sinica*26: 1037-1060.**GA-CKPLS**: R code for “Predicting disease trait with genomic data: A composite kernel approach”.

**Reference**: Yang, H.T., S. Li, H. Cao,
C. Zhang and Y. Cui. (2016). Predicting disease trait with genomic data: A
composite kernel approach. *Briefings in
Bioinformatics *(in press)

**VC-sPCR**: R code for “A nonlinear model for gene-based gene-environment interaction”.

[VC-sPCR.rar];

**Reference**: Sa, J., X. Liu, T. He, G.
Liu and Y. Cui. (2016). A nonlinear
model for gene-based gene-environment interaction.* *17(6): 882.

**IVGC**: R code for “Integrative analysis of genetical genomics incorporating network structures”.

[check github];

**Reference**: Gao, B., X. Liu, H. Li and
Y. Cui. (2019). Integrative analysis of genetical genomics incorporating
network structures. *Biometrics *(in
press)

*Last
Modified May, 2018*