iFad: An integrative factor analysis model for drug-pathway association inference

This package implements a Bayesian sparse factor model for the joint analysis of paired datasets, one is the gene expression dataset and the other is the drug sensitivity profiles, measured across the same panel of samples, e.g., cell lines. Prior knowledge about gene-pathway associations can be easily incorporated in the model to aid the inference of drug-pathway associations.

AuthorHaisu Ma <haisu.ma.pku.2008@gmail.com>
Date of publication2014-03-27 23:58:34
MaintainerHaisu Ma <haisu.ma.pku.2008@gmail.com>
LicenseGPL (>= 2)
Version3.0

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Man pages

data_simulation: Simulation of example dataset for the factor analysis model

gibbs_sampling: Gibbs sampling for the inference of the inference of...

iFad-package: An integrative factor analysis model for drug-pathway...

label_chain: Updated factor label configuration during the Gibbs sampling

matrixL1: The matrix representing prior belief for matrixZ1

matrixL2: The matrix representing prior belief for matrixZ2

matrixPi1: The bernoulli probability matrix for matrixZ1

matrixPi2: The bernoulli probability matrix for matrixZ2

matrixPr_chain: The updated posterior probability for matrixZ1&Z2 during...

matrixW1: The factor loading matrix representing the gene-pathway...

matrixW2: The factor loading matrix representing the drug-pathway...

matrixW_chain: The updated matrixW during the Gibbs sampling

matrixX: The factor activity matrix

matrixX_chain: The updated matrixX in the Gibbs sampling process

matrixY1: The gene expression dataset

matrixY2: The drug sensitivity matrix

matrixZ1: The binary indicator matrix for matrixW1

matrixZ2: Binary indictor matrix for matrixW2

matrixZ_chain: The updated matrixZ in the Gibbs sampling process

mcmc_trace_plot: Traceplot of the Gibbs sampling iterations

ROC_plot: Calculate the AUC (area under curve) and generate ROC plot

sigma1: Covariance matrix of the noise term for the genes

sigma2: Covariance matrix of the noise term for the drugs

tau_g_chain: The updated tau_g in the Gibbs sampling process

Y1_mean: The mean value used for the simulation of matrixY1

Y2_mean: The mean value used for the simulation of matrixY2

Ymean_compare: Compare the infered Y_mean values with the true values

Files in this package

iFad
iFad/NAMESPACE
iFad/data
iFad/data/matrixX.rda
iFad/data/matrixW_chain.rda
iFad/data/matrixW2.rda
iFad/data/matrixPr_chain.rda
iFad/data/matrixL2.rda
iFad/data/Y2_mean.rda
iFad/data/matrixPi1.rda
iFad/data/matrixZ_chain.rda
iFad/data/tau_g_chain.rda
iFad/data/Y1_mean.rda
iFad/data/matrixZ2.rda
iFad/data/matrixPi2.rda
iFad/data/matrixY1.rda
iFad/data/sigma2.rda
iFad/data/matrixX_chain.rda
iFad/data/matrixW1.rda
iFad/data/matrixZ1.rda
iFad/data/label_chain.rda
iFad/data/matrixY2.rda
iFad/data/sigma1.rda
iFad/data/matrixL1.rda
iFad/R
iFad/R/data_simulation.R iFad/R/Ymean_compare.R iFad/R/ROC_plot.R iFad/R/mcmc_trace_plot.R iFad/R/gibbs_sampling.R
iFad/MD5
iFad/DESCRIPTION
iFad/man
iFad/man/matrixW1.Rd iFad/man/matrixPr_chain.Rd iFad/man/matrixZ_chain.Rd iFad/man/Y2_mean.Rd iFad/man/label_chain.Rd iFad/man/matrixX_chain.Rd iFad/man/tau_g_chain.Rd iFad/man/matrixX.Rd iFad/man/Y1_mean.Rd iFad/man/iFad-package.Rd iFad/man/matrixL2.Rd iFad/man/matrixL1.Rd iFad/man/sigma1.Rd iFad/man/matrixY2.Rd iFad/man/data_simulation.Rd iFad/man/matrixW_chain.Rd iFad/man/matrixW2.Rd iFad/man/ROC_plot.Rd iFad/man/matrixPi1.Rd iFad/man/sigma2.Rd iFad/man/matrixZ1.Rd iFad/man/matrixPi2.Rd iFad/man/mcmc_trace_plot.Rd iFad/man/gibbs_sampling.Rd iFad/man/matrixZ2.Rd iFad/man/Ymean_compare.Rd iFad/man/matrixY1.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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