From marginal study summaries to synthetic patients15 days ago
Input | Probability and generation | Independent groups and limitations
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From marginal study summaries to synthetic patients15 days ago
Input | Probability and generation | Independent groups and limitations
Bivariate Logistic Box-Cox Regression with mvboxcox2 months ago
Introduction | Installation | Model | Interpreting the parameters | Weak-signal interpretation | Simulate, fit, and predict | Built-in NHANES data | Sampling-weighted fitting | Main functions | References
Introduction to the iimi package11 months ago
1. Introduction | 1.1. Installation | 1.2. Loading packages and data | 1.3. Data Pre-processing | 2. Converting BAM file(s) into coverage profiles and feature-extracted data frame | 2.1. State the path to the folder of your BAM files | 2.2. Create a data frame that contains the coverage profiles. | 2.2.1. Convert BAM files to a list of RLEs. | 2.2.2. Convert the list of RLEs to a feature-extracted data frame. | 3. Predicting the plant sample(s) | 3.1 Using pre-trained models and no customization | 3.2. Customizing your own model | 3.3. Customizing unreliable regions | 3.3.1. Mappability profile | 3.3.2. High nucleotide content regions | 4. Visualizing the coverage profiles | 5. References