340 citations · 1k across the 21 of their papers we have counts for
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stat.CO2017★ 10 cited
varbvs: Fast Variable Selection for Large-scale Regression
Peter Carbonetto, Xiang Zhou, Matthew Stephens
We introduce varbvs, a suite of functions written in R and MATLAB for regression analysis of large-scale data sets using Bayesian variable selection methods. We have developed nume…
stat.ME2017★ 15 cited
Empirical Bayes Shrinkage and False Discovery Rate Estimation, Allowing For Unwanted Variation
David Gerard, Matthew Stephens
We combine two important ideas in the analysis of large-scale genomics experiments (e.g. experiments that aim to identify genes that are differentially expressed between two condit…
stat.ME2017★ 6 cited
Unifying and Generalizing Methods for Removing Unwanted Variation Based on Negative Controls
David Gerard, Matthew Stephens
Unwanted variation, including hidden confounding, is a well-known problem in many fields, particularly large-scale gene expression studies. Recent proposals to use control genes --…