Contents | Introduction to SPsimSeq | Installing SPsimSeq | Demonstration | Example 1: simulating bulk RNA-seq | Example 2: simulating single-cell RNA-seq (containing read-counts) | References

Obtaining the original data | Processing the drug similarities | Obtaining the data | Calculating the similarities

Concepts and terms used in the package. | Notation and naming of networks in the package | Data in the package | Homogeneous networks | Heterogeneous networks | Fitting a two-step kernel ridge regression | Heterogeneous network | Homogeneous network | Extracting parameters from a trained model. | Information on the fit of the model | Performing leave-one-out cross-validation | Settings for LOO | Use LOO in other functions | Looking at model output | Tuning a model to find the best lambda. | Predicting new values | Predict for new K-nodes | Predict for new G-nodes | Predict for new K and G nodes | Impute new values based on a tskrr model

Virtual classes | Actual classes | Inheritance from tskrr | Slots defined by tskrrHomogeneous | Slots defined by tskrrHeterogeneous | Inheritance from tskrrTune | Inheritance from tskrrImpute

Introduction | Standard PIM | More complicated examples | Relationship to rank tests | Remarks

Introduction | Usage | Graphical tools | Additional information