:: DESCRIPTION
GWASelect implements a novel variable selection method for GWAS (Genomewide Association Studies) data and is able to handle more than half million SNPs.
::DEVELOPER
:: SCREENSHOTS
N/A
::REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Q. He and D.Y. Lin.
A variable selection method for genome-wide association studies.
Bioinformatics (2010)doi: 10.1093/bioinformatics/btq600
:: DESCRIPTION
netVar is a network-based method that uses the gene connectivity in the gene co-expression network for variable selection.
::DEVELOPER
the Liu Lab , The UT Health Science Center at Houston.
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2014 May 20;15(1):153.
Improving the sensitivity of sample clustering by leveraging gene co-expression networks in variable selection.
Wang Z, Lucas FA, Qiu P, Liu Y.
:: DESCRIPTION
gboosting is an R package for conducting GWAS with survival outcomes using Boosting and FDR control methods
::DEVELOPER
Big-data Evaluation and Statistics Team (BEST)
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates.
He K, Li Y, Zhu J, Liu H, Lee JE, Amos CI, Hyslop T, Jin J, Lin H, Wei Q, Li Y.
Bioinformatics. 2015 Sep 17. pii: btv517.
