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  "Title": "Tools for Adaptive Immune Receptor Sequence-Based Machine and\nDeep Learning",
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  "Description": "A set of tools to for machine and deep learning in R from\namino acid and nucleotide sequences focusing on adaptive immune\nreceptors. The package includes pre-processing of sequences,\nunifying gene nomenclature usage, encoding sequences, and\ncombining models. This package will serve as the basis of\nfuture immune receptor sequence functions/packages/models\ncompatible with the scRepertoire ecosystem.",
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    "summaryMatrix",
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      "title": "ACE Richness Estimator",
      "topics": [
        "ace_richness"
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    },
    {
      "page": "adjacencyMatrix",
      "title": "Adjacency Matrix From Amino Acid or Nucleotide Sequences",
      "topics": [
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    {
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      "title": "Standard 20 amino acids",
      "topics": [
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    {
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      "title": "Build Edit Distance Network",
      "topics": [
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    {
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      "title": "Positional Entropy / Diversity Biological Sequences",
      "topics": [
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      ]
    },
    {
      "page": "calculateFrequency",
      "title": "Relative Residue Frequencies at Every Position",
      "topics": [
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      ]
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      "topics": [
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      ]
    },
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      "title": "Motif Enumeration and Counting",
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      "title": "Position-wise Amino-Acid Property Profiles",
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    {
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      "title": "D50 Dominance Index",
      "topics": [
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    },
    {
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      "title": "Dxx Dominance Index",
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    {
      "page": "formatGenes",
      "title": "Ensure clean gene nomenclature using IMGT annotations",
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      "title": "Get IMGT Sequences for Specific Loci",
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      "title": "Extract Immune Receptor Sequences",
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      "title": "Infer CDR-loop segments from V-gene calls",
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      "title": "Inverse Simpson Diversity",
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      "title": "Randomly Mutate Sequences of Amino Acids",
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      "title": "Generate Sinusoidal Positional Encodings",
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      "title": "Fast Matrix Scaling or Transformation",
      "topics": [
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      "title": "Decode Amino Acid or Nucleotide Sequences",
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      "title": "Universal Amino-acid Sequence Encoder",
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        "propertyEncoder",
        "sequenceEncoder"
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      "title": "Shannon Diversity Index (Entropy)",
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    {
      "page": "summaryMatrix",
      "title": "Fast Matrix Summaries",
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      "title": "Generate Tokenized Sequences from Amino Acid String",
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      "filename": "immApex.html",
      "title": "Machine and Deep Learning Models with immApex",
      "author": "Nick Borcherding",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Loading Libraries",
        "Acquiring and Preparing Repertoire Data",
        "getIMGT",
        "formatGenes",
        "inferCDR",
        "Generating and Augmenting Sequence Sets",
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        "Example 2: Unsupervised Clustering with PCA and Geometric Encoding",
        "Example 3: Identifying Sequence Communities with Network Analysis",
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      "created": "2024-08-05 17:39:54",
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