FacPad: Bayesian Sparse Factor Analysis model for the inference of pathways responsive to drug treatment
Version 3.0

This method tries to explain the gene-wise treatment response ratios in terms of the latent pathways. It uses bayesian sparse factor modeling to infer the loadings (weights) of each pathway on its associated probesets as well as the latent factor activity levels for each treatment.

AuthorHaisu Ma
Date of publication2014-03-28 00:31:36
MaintainerHaisu Ma <haisu.ma.pku.2008@gmail.com>
LicenseGPL (>= 2)
Version3.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("FacPad")

Getting started

Package overview

Popular man pages

FacPad-package: Sparse factor modeling for the inference of drug-responsive...
gibbs2: A Collapsed Gibbs Sampling Algorithm for the Inference of...
gibbs_sampling: A Collapsed Gibbs Sampling Algorithm for the Inference of...
matrixL: Pathway structure matrix L
matrixY: The treatment response matrix
See all...

All man pages Function index File listing

Man pages

FacPad-package: Sparse factor modeling for the inference of drug-responsive...
gibbs2: A Collapsed Gibbs Sampling Algorithm for the Inference of...
gibbs_sampling: A Collapsed Gibbs Sampling Algorithm for the Inference of...
matrixL: Pathway structure matrix L
matrixY: The treatment response matrix

Functions

Files

NAMESPACE
data
data/matrixL.rda
data/matrixY.rda
R
R/gibbs_sampling.R
R/gibbs2.R
MD5
DESCRIPTION
man
man/FacPad-package.Rd
man/matrixL.Rd
man/matrixY.Rd
man/gibbs2.Rd
man/gibbs_sampling.Rd
FacPad documentation built on May 20, 2017, 5:39 a.m.

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