Load packages | Load required datasets | Heatmap of simulated feature set | Search for a subset of genomic features that are likely associated with a functional response of interest using each of the scoring methods | 1. Kolmogorov-Smirnov Scoring Method | 2. Wilcoxon Rank-Sum Scoring Method | 3. Conditional Mutual Information Scoring Method from REVEALER | 4. K-Nearest Neighbor Mutual Information Estimator from knnmi package | 5. Correlation Scoring Method | 6. Custom - An User Defined Scoring Method | SessionInfo

Software requirements | Build Docker image of CaDrA | (1) Clone this repository | (2) Navigate to CaDrA folder where Dockerfile is stored and build its Docker image. | (3) After the build is completed, check if the image is built successfully | Run CaDrA container with its built image | Run CaDrA on RStudio Server hosted within a Docker environment

Load packages | Load required datasets | Find a subset of features that maximally associated with a given outcome of interest | Visualize best meta-features result | Perform permutation-based testing | Visualize permutation result | SessionInfo