Man pages for andreaskapou/mpgex
Methylation Profiles predict Gene Expression
| blm | Fitting linear models using Basis Functions |
| bpr_control_data | Synthetic control data for mpgex package |
| bpr_data | Synthetic data for mpgex package |
| bpr_EM | EM algorithm for BPR mixture model |
| bpr_fdmm | Gibbs sampling algorithm for BPR mixture model |
| bpr_gibbs | Generic function for performing Gibbs sampling on BPR model |
| bpr_gibbs.list | Gibbs sampling for the BPR model using list x |
| bpr_gibbs.matrix | Gibbs sampling for the BPR model using list x |
| bpr_gradient | Gradient of the BPR log likelihood function |
| bpr_likelihood | BPR log likelihood function |
| bpr_optim | Generic function for optimizing BPR negative log likelihood... |
| bpr_optim.list | Optimization method for the BPR NLL function using list x |
| bpr_optim.matrix | Optimization method for the BPR NLL using matrix x |
| bpr_treatment_data | Synthetic treatment data for mpgex package |
| calculate_errors | Calculate error metrics |
| design_matrix | Generic function for creating a design matrix H |
| design_matrix.polynomial | Create polynomial design matrix H |
| design_matrix.rbf | Creates an RBF design matrix H |
| eval_function | Generic function for evaluating basis functions |
| eval_function.polynomial | Evaluate polynomial function |
| eval_function.rbf | Evaluate rbf function |
| eval_probit_function | Generic function for evaluating probit basis functions |
| gex_control_data | Synthetic control data for mpgex package |
| gex_data | Synthetic data for mpgex package |
| gex_treatment_data | Synthetic treatment data for mpgex package |
| learn_diff_meth | Learn differential methylation profiles using BLM |
| log_sum_exp | Compute stable Log-Sum-Exp |
| minmax_scaling | Compute the min-max scaling |
| mpgex | 'mpgex': Package for predicting gene expression from... |
| mpgex_cluster | Cluster similar methylation profiles |
| mpgex_cluster_bayes | Cluster similar methylation profiles using Gibbs smapling |
| mpgex_differential_regr | Predict simple differntial gene expression from differential... |
| mpgex_diff_regr | Predict differntial gene expression from differential... |
| mpgex_regr | Predict gene expression from methylation profiles |
| mpgex_regr_bayes | Predict gene expression from methylation profiles using Gibbs... |
| partition_data | Partition data in train and test set |
| plot_diff_mpgex | Plot method for differential methylation |
| plot_fitted_profiles | Plot fit of methylation profiles across a region |
| plot.mpgex_diff_regr | Plot method for differential methylation |
| plot.polynomial | S3 plot method for polynomial objects |
| plot.rbf | S3 plot method for rbf objects |
| polynomial_basis | Apply polynomial basis function. |
| polynomial.object | Creates a polynomial object |
| predict.blm | Make predictions using the Basis Linear Model |
| predict_model_gex | Predict gene expression data from methylation profiles |
| print.blm | Print the output of the Basis Linear Model |
| print.summary.blm | Print summary output of the Basis Linear Model |
| rbf_basis | Apply radial basis function |
| rbf.object | Creates an RBF object |
| summary.blm | Summary output of the Basis Linear Model |
| sum_weighted_bpr_grad | Sum of weighted gradients of the BPR log likelihood |
| sum_weighted_bpr_lik | Sum of weighted BPR log likelihoods |
| train_model_gex | Train model for gene expression data from methylation... |
