From e22dd7b349481ed75802ee98ddc696d56dbb7f5f Mon Sep 17 00:00:00 2001 From: Yang lab Date: Tue, 13 Dec 2016 14:07:55 +0800 Subject: [PATCH 1/4] Update README.md --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index 393b8ec..8b7d5a3 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,10 @@ library(IGESS) help(package="IGESS")   ##Development + +This R package is developed by Mingwei Dai and Can Yang. + +##Installation To install the development version of IGESS, it's easiest to use the 'devtools' package. Note that IGESS depends on the 'Rcpp' and 'RcppArmadillo' package, which also requires appropriate setting of Rtools and Xcode for Windows and Mac OS/X, respectively. install.packages("devtools") @@ -17,6 +21,7 @@ library(devtools) install_github("daviddaigithub/IGESS") ##References +M. Dai, J. Ming, M., Cai, J. Liu, C. Yang, X. Wan, and Z. Xu. IGESS: A statistical approach to integrating individual level genotype data and summary statistics in genome wide association studies. ======= # IGESS From 71e409d2a170369493cda16bdf71be9536c33b35 Mon Sep 17 00:00:00 2001 From: Yang lab Date: Tue, 13 Dec 2016 14:09:16 +0800 Subject: [PATCH 2/4] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8b7d5a3..1a164ae 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ help(package="IGESS")   ##Development -This R package is developed by Mingwei Dai and Can Yang. +This R package is developed by Mingwei Dai and Can Yang, and maintained by Can Yang . ##Installation To install the development version of IGESS, it's easiest to use the 'devtools' package. Note that IGESS depends on the 'Rcpp' and 'RcppArmadillo' package, which also requires appropriate setting of Rtools and Xcode for Windows and Mac OS/X, respectively. From 8e473ff5b0c746eaf4a958055d2e16554d23f05a Mon Sep 17 00:00:00 2001 From: Yang lab Date: Fri, 15 Sep 2017 21:22:59 +0800 Subject: [PATCH 3/4] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 1a164ae..bfb65c5 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,5 @@ -#IGESS +IGESS +======= IGESS is a statistical approach to integrating individual level genotype data and summary statistics in Genome Wide Association Studies. 'IGESS' R package provides computationally efficient and user friendly interface to fit and evaluate the IGESS model. It accepts both the R-type data and binary plink files. From dfe9919a1af89dae67b0b78dbd48c0ab6d747127 Mon Sep 17 00:00:00 2001 From: Yang lab Date: Fri, 15 Sep 2017 21:24:46 +0800 Subject: [PATCH 4/4] Update README.md --- README.md | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index bfb65c5..a0e285c 100644 --- a/README.md +++ b/README.md @@ -3,26 +3,29 @@ IGESS IGESS is a statistical approach to integrating individual level genotype data and summary statistics in Genome Wide Association Studies. 'IGESS' R package provides computationally efficient and user friendly interface to fit and evaluate the IGESS model. It accepts both the R-type data and binary plink files. -##Usage +Usage +======= The following two help pages provide a good start point for the genetic analysis using IGESS package, including the overview of IGESS package and the example command lines: library(IGESS) help(package="IGESS")   -##Development - +Development +======= This R package is developed by Mingwei Dai and Can Yang, and maintained by Can Yang . -##Installation +Installation +======= To install the development version of IGESS, it's easiest to use the 'devtools' package. Note that IGESS depends on the 'Rcpp' and 'RcppArmadillo' package, which also requires appropriate setting of Rtools and Xcode for Windows and Mac OS/X, respectively. install.packages("devtools") library(devtools) install_github("daviddaigithub/IGESS") -##References -M. Dai, J. Ming, M., Cai, J. Liu, C. Yang, X. Wan, and Z. Xu. IGESS: A statistical approach to integrating individual level genotype data and summary statistics in genome wide association studies. +References +======= +M. Dai, J. Ming, M., Cai, J. Liu, C. Yang, X. Wan, and Z. Xu. IGESS: A statistical approach to integrating individual level genotype data and summary statistics in genome wide association studies. Bioinformatics. 2017 Sep 15;33(18):2882-2889. doi: 10.1093/bioinformatics/btx314 ======= # IGESS