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  "Title": "An R package for colorectal cancer screening and microbiome\nanalysis",
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  "Description": "A developed and benchmarked reproducible machine learning\nframework for microbiome-based colorectal cancer (CRC)\nscreening. By systematically evaluating normalization\nstrategies, taxonomic resolutions, and class imbalance\nhandling. This R package allows users to apply the full\npipeline or selectively run specific components depending on\ntheir analytical needs. It establishes a scalable foundation\nfor developing interpretable microbiome-based screening tools\nto support early CRC detection. This approach could be easily\nimplemented in a national screening programme, to improve early\ndetection rates for this disease.",
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      "topics": [
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      "title": "Create a CrcBiomeScreen S4 object for microbiome-based CRC analysis",
      "topics": [
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      "title": "Create a CrcBiomeScreen object from TreeSummarizedExperiment",
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      "title": "Evaluate the performance of model predictions",
      "topics": [
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      "title": "Accessor for AbsoluteAbundance slot of CrcBiomeScreen object",
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      "title": "Accessor for NormalizedData slot of CrcBiomeScreen object",
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      "title": "Accessor for RelativeAbundance slot of CrcBiomeScreen object",
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        "getRelativeAbundance,CrcBiomeScreen-method"
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      "topics": [
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        "getSampleData",
        "getSampleData,CrcBiomeScreen-method"
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      "title": "Accessor for TaxaData slot of CrcBiomeScreen object",
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        "getTaxaData,CrcBiomeScreen-method"
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      "title": "Accessor for TaxaLevelData slot",
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        "getTaxaLevelData,CrcBiomeScreen-method"
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      "topics": [
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      "page": "setNormalizedData-setter",
      "title": "setNormalizedData<-: Setter for NormalizedData slot of CrcBiomeScreen object",
      "topics": [
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        "setNormalizedData<-",
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      "source": "CrcBiomeScreen.Rmd",
      "filename": "CrcBiomeScreen.html",
      "title": "CrcBiomeScreen: Colorectal Cancer Microbiome Screening and Analysis",
      "author": "Chengxin Li",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Installation",
        "Getting started",
        "Exploring the data structure",
        "Data preparation",
        "Taxonomic data processing",
        "Supported formats",
        "Original taxa column",
        "Special handling of uncultured and unclassified",
        "Choosing a Taxonomic Level",
        "Handling Data Without Taxonomic Strings",
        "Data normalization",
        "> Move to: Full-scale modeling workflow using real cohort data for reference",
        "Runnable toy workflow setup",
        "Setup the toy dataset",
        "Model training and evaluation",
        "External validation",
        "Full screening workflow in one step",
        "Get the the raw prediction scores for each sample",
        "Full-scale modeling workflow using real cohort data for reference",
        "Data filtering and splitting",
        "Quality control",
        "Model training and Evaluation",
        "Prediction & Evaluation",
        "Step 1: Predict on New Data",
        "Step 2: Evaluate Model Performance",
        "Streamlined Screening Workflow",
        "Best practices and recommendations",
        "Normalization method selection",
        "Model selection",
        "Validation strategies",
        "Class imbalance",
        "Troubleshooting",
        "Common issues and solutions",
        "Feature mismatch between datasets",
        "Memory issues with large datasets",
        "Session information",
        "References"
      ],
      "created": "2025-09-03 16:01:26",
      "modified": "2026-07-16 10:20:33",
      "commits": 43
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