The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

adaptMT

Overview

This package implements Adaptive P-Value Thresholding in the paper: AdaPT: An interactive procedure for multiple testing with side information. It includes both a framework that allows the user to specify any algorithm to learn local FDR and a pool of convenient functions that implement specific algorithms:

• adapt() provides a generic framework of AdaPT permitting any learning algorithm;
• adapt_glm(), adapt_gam() and adapt_glmnet() provide convenient wrappers of AdaPT using Generalized Linear Models (GLM), Generalized Additive Models (GAM) and L1-penalized GLMs;

Install the adaptMT package then read vignette(“adapt_demo”, package = “adaptMT”).

Installation

# install.packages("devtools")
devtools::install_github("lihualei71/adaptMT")

If one wants to access the vignette, run the following code to build the vignette. This might update other related packages and please be patient if so.

devtools::install_github("lihualei71/adaptMT", build_vignettes = TRUE)

An Example

We illustrate the usage of adaptMT package using the example discussed in Section 5.1 of the paper AdaPT: An interactive procedure for multiple testing with side information.

# Load package
library("adaptMT")

# Load data
data(estrogen)
pvals <- as.numeric(estrogen$pvals)
x <- data.frame(x = as.numeric(estrogen$ord_high))

# Define the exponential family for AdaPT (Section 4)
dist <- beta_family()

# Run adapt_glm
library("splines")
formulas <- paste0("ns(x, df = ", 6:10, ")")
res <- adapt_glm(x = x, pvals = pvals, pi_formulas = formulas,
                 mu_formulas = formulas, dist = dist, nfits = 10)

# Plot the threshold curve and the level curves of local FDR
plot_1d_thresh(res, alpha = 0.1, "P-Value Thresholds")
plot_1d_lfdr(res, alpha = 0.1, "Level Curves of Local FDR Estimates")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.