Man pages for iFad
An integrative factor analysis model for drug-pathway association inference
| 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 |
