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

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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.

Author
Haisu Ma <haisu.ma.pku.2008@gmail.com>
Date of publication
2014-03-27 23:58:34
Maintainer
Haisu Ma <haisu.ma.pku.2008@gmail.com>
License
GPL (>= 2)
Version
3.0

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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