Pinned Repositories
agg_utility
Source code for the R Shiny app associated with the paper "A multi-gene, multi-disease uncertainty utility for selecting genes for panel testing".
AggreMendMod
Reproduce the results presented in the paper "Evaluating Mendelian risk prediction models that aggregate across genes and cancers".
Annals_of_Surgery_Gender
code_review_solutions
hi
FaSTLMM.jl
Julia implementation of Factored Spectrally Transformed Linear Mixed Models
lab6_exercise
Practice collaborative workflow in git. Also practice programatic data retrieval and verification
NAFLD_superlearner
Reproduce the results presented in the paper "Novel machine learning approaches to the non-invasive diagnosis of liver fibrosis in NAFLD"
PanelRePROducible
Reproduce the results presented in the paper "Statistical methods for Mendelian models with multiple genes and cancers".
MatrixLM.jl
Core functions to obtain closed-form least squares estimates for matrix linear models.
MatrixLMnet.jl
Core functions to obtain L1-L2 penalized estimates for matrix linear models.
janewliang's Repositories
janewliang/PanelRePROducible
Reproduce the results presented in the paper "Statistical methods for Mendelian models with multiple genes and cancers".
janewliang/agg_utility
Source code for the R Shiny app associated with the paper "A multi-gene, multi-disease uncertainty utility for selecting genes for panel testing".
janewliang/AggreMendMod
Reproduce the results presented in the paper "Evaluating Mendelian risk prediction models that aggregate across genes and cancers".
janewliang/Annals_of_Surgery_Gender
janewliang/code_review_solutions
hi
janewliang/FaSTLMM.jl
Julia implementation of Factored Spectrally Transformed Linear Mixed Models
janewliang/lab6_exercise
Practice collaborative workflow in git. Also practice programatic data retrieval and verification
janewliang/NAFLD_superlearner
Reproduce the results presented in the paper "Novel machine learning approaches to the non-invasive diagnosis of liver fibrosis in NAFLD"
janewliang/project-alpha