Machine and Deep Learning Models with immApex
Introduction | Loading Libraries | Acquiring and Preparing Repertoire Data | getIMGT | formatGenes | inferCDR | Generating and Augmenting Sequence Sets | generateSequences | mutateSequences | Feature Engineering from Repertoires | calculateFrequency | calculateEntropy | calculateProperty | calculateGeneUsage | calculateMotif | probabilityMatrix | adjacencyMatrix | buildNetwork | Basic Usage | Standard BCR/TCR Network | Finding Clonotypes with V Gene Filtering | Encoding Sequences for Model Input | sequenceEncoder | onehotEncoder | propertyEncoder | geometricEncoder | tokenizeSequences | sequenceDecoder | Training a Model | Example 1: Classifying Sequences with Random Forest | Example 2: Unsupervised Clustering with PCA and Geometric Encoding | Example 3: Identifying Sequence Communities with Network Analysis | Conclusion | Session Info