{
  "_id": "6ad1f1c3a6a61792ed76c24f",
  "Package": "glyclean",
  "Title": "Perform Preprocessing on Glycomics and Glycoproteomics Data",
  "Version": "0.16.0",
  "Authors@R": "person(\"Bin\", \"Fu\", , \"23110220018@m.fudan.edu.cn\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-8567-2997\"))",
  "Description": "Provides comprehensive data preprocessing tools for\nglycomics and glycoproteomics experiments. The package offers\nboth automated and manual preprocessing pipelines, including\nnormalization (median, quantile, vsn, total area), missing\nvalue handling (filtering, imputation using various methods),\nbatch effect correction (using ComBat and other methods), data\naggregation (at peptide, glycan, or site level), and quality\ncontrol functions. The automated pipeline intelligently selects\nappropriate methods based on data characteristics and sample\nsize, making it easy to prepare clean, analysis-ready data for\ndownstream statistical analysis within the glycoverse\necosystem. Works seamlessly with 'glyexp::GlycomicSE',\n'glyexp::GlycoproteomicSE', and\n'SummarizedExperiment::SummarizedExperiment' objects to ensure\ndata consistency and interoperability.",
  "License": "MIT + file LICENSE",
  "Config/testthat/edition": "3",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.3",
  "URL": "https://glycoverse.github.io/glyclean/",
  "VignetteBuilder": "knitr",
  "Config/pak/sysreqs": "libglpk-dev libicu-dev libpng-dev libxml2-dev\nlibssl-dev zlib1g-dev",
  "Repository": "https://glycoverse.r-universe.dev",
  "Date/Publication": "2026-10-15 17:29:57 UTC",
  "RemoteUrl": "https://github.com/glycoverse/glyclean",
  "RemoteRef": "v0.16.0",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-10-16 08:29:51 UTC",
    "User": "root"
  },
  "Author": "Bin Fu [aut, cre] (ORCID: <https://orcid.org/0000-0001-8567-2997>)",
  "Maintainer": "Bin Fu <23110220018@m.fudan.edu.cn>",
  "_user": "glycoverse",
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  "_expires": "2027-01-24T09:43:29.000Z",
  "_created": "2026-10-16T08:29:51.000Z",
  "_published": "2026-10-16T09:43:31.214Z",
  "_buildurl": "https://github.com/r-universe/glycoverse/actions/runs/38873459896",
  "_status": "success",
  "_host": "GitHub-Actions",
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    "author": "Bin Fu <65430559+fubin1999@users.noreply.github.com>",
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    "message": "chore: release version 0.16.0 (#32)",
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    "description": "A modern glycomics and glycoproteomics data analysis framework in R."
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  "_exports": [
    "add_site_seq",
    "adjust_protein",
    "aggregate",
    "auto_aggregate",
    "auto_clean",
    "auto_coda",
    "auto_correct_batch_effect",
    "auto_impute",
    "auto_normalize",
    "auto_remove",
    "correct_batch_effect",
    "detect_batch_effect",
    "impute_bpca",
    "impute_fw_knn",
    "impute_half_sample_min",
    "impute_min_prob",
    "impute_miss_forest",
    "impute_ppca",
    "impute_sample_min",
    "impute_svd",
    "impute_sw_knn",
    "impute_zero",
    "normalize_loesscyc",
    "normalize_loessf",
    "normalize_median",
    "normalize_median_abs",
    "normalize_median_quotient",
    "normalize_quantile",
    "normalize_rlr",
    "normalize_rlrma",
    "normalize_rlrmacyc",
    "normalize_total_area",
    "normalize_vsn",
    "plot_batch_pca",
    "plot_cv_dent",
    "plot_int_boxplot",
    "plot_missing_bar",
    "plot_missing_heatmap",
    "plot_rank_abundance",
    "plot_rep_scatter",
    "plot_rle",
    "plot_tic_bar",
    "remove_constant",
    "remove_low_cv",
    "remove_low_expr",
    "remove_low_var",
    "remove_rare",
    "transform_alr",
    "transform_clr"
  ],
  "_help": [
    {
      "page": "add_site_seq",
      "title": "Add site-specific sequence information.",
      "topics": [
        "add_site_seq",
        "add_site_seq.default",
        "add_site_seq.glyexp_experiment"
      ]
    },
    {
      "page": "adjust_protein",
      "title": "Adjust Protein Expression",
      "topics": [
        "adjust_protein",
        "adjust_protein.default",
        "adjust_protein.glyexp_experiment"
      ]
    },
    {
      "page": "aggregate",
      "title": "Aggregate Data",
      "topics": [
        "aggregate",
        "glyclean_aggregate.default",
        "glyclean_aggregate.glyexp_experiment"
      ]
    },
    {
      "page": "auto_clean",
      "title": "Automatic Data Preprocessing",
      "topics": [
        "auto_clean"
      ]
    },
    {
      "page": "auto_coda",
      "title": "Automatical CoDA transformation",
      "topics": [
        "auto_coda"
      ]
    },
    {
      "page": "auto_correct_batch_effect",
      "title": "Automatic Batch Correction",
      "topics": [
        "auto_correct_batch_effect"
      ]
    },
    {
      "page": "auto_impute",
      "title": "Automatic Imputation",
      "topics": [
        "auto_impute"
      ]
    },
    {
      "page": "auto_normalize",
      "title": "Automatic Normalization",
      "topics": [
        "auto_normalize"
      ]
    },
    {
      "page": "auto_remove",
      "title": "Automatic Removing Variables",
      "topics": [
        "auto_remove"
      ]
    },
    {
      "page": "correct_batch_effect",
      "title": "Correct Batch Effect",
      "topics": [
        "correct_batch_effect"
      ]
    },
    {
      "page": "detect_batch_effect",
      "title": "Detect batch effect",
      "topics": [
        "detect_batch_effect"
      ]
    },
    {
      "page": "impute_bpca",
      "title": "BPCA Imputation",
      "topics": [
        "impute_bpca"
      ]
    },
    {
      "page": "impute_fw_knn",
      "title": "Feature-wise KNN Imputation",
      "topics": [
        "impute_fw_knn"
      ]
    },
    {
      "page": "impute_half_sample_min",
      "title": "Half Sample Minimum Imputation",
      "topics": [
        "impute_half_sample_min"
      ]
    },
    {
      "page": "impute_min_prob",
      "title": "Minimum Probability Imputation",
      "topics": [
        "impute_min_prob"
      ]
    },
    {
      "page": "impute_miss_forest",
      "title": "MissForest Imputation",
      "topics": [
        "impute_miss_forest"
      ]
    },
    {
      "page": "impute_ppca",
      "title": "PPCA Imputation",
      "topics": [
        "impute_ppca"
      ]
    },
    {
      "page": "impute_sample_min",
      "title": "Sample Minimum Imputation",
      "topics": [
        "impute_sample_min"
      ]
    },
    {
      "page": "impute_svd",
      "title": "SVD Imputation",
      "topics": [
        "impute_svd"
      ]
    },
    {
      "page": "impute_sw_knn",
      "title": "Sample-wise KNN Imputation",
      "topics": [
        "impute_sw_knn"
      ]
    },
    {
      "page": "impute_zero",
      "title": "Zero Imputation",
      "topics": [
        "impute_zero"
      ]
    },
    {
      "page": "normalize_loesscyc",
      "title": "LoessCyc Normalization",
      "topics": [
        "normalize_loesscyc"
      ]
    },
    {
      "page": "normalize_loessf",
      "title": "LoessF Normalization",
      "topics": [
        "normalize_loessf"
      ]
    },
    {
      "page": "normalize_median",
      "title": "Median Normalization",
      "topics": [
        "normalize_median"
      ]
    },
    {
      "page": "normalize_median_abs",
      "title": "Absolute Median Normalization",
      "topics": [
        "normalize_median_abs"
      ]
    },
    {
      "page": "normalize_median_quotient",
      "title": "Median Quotient Normalization",
      "topics": [
        "normalize_median_quotient"
      ]
    },
    {
      "page": "normalize_quantile",
      "title": "Quantile Normalization",
      "topics": [
        "normalize_quantile"
      ]
    },
    {
      "page": "normalize_rlr",
      "title": "Robust Linear Regression Normalization",
      "topics": [
        "normalize_rlr"
      ]
    },
    {
      "page": "normalize_rlrma",
      "title": "Robust Linear Regression with Median Adjustment Normalization",
      "topics": [
        "normalize_rlrma"
      ]
    },
    {
      "page": "normalize_rlrmacyc",
      "title": "Robust Linear Regression with Median Adjustment and Cyclic Normalization",
      "topics": [
        "normalize_rlrmacyc"
      ]
    },
    {
      "page": "normalize_total_area",
      "title": "Total Area Normalization",
      "topics": [
        "normalize_total_area"
      ]
    },
    {
      "page": "normalize_vsn",
      "title": "Variance Stabilizing Normalization",
      "topics": [
        "normalize_vsn"
      ]
    },
    {
      "page": "plot_batch_pca",
      "title": "Plot PCA Score by Batch",
      "topics": [
        "plot_batch_pca"
      ]
    },
    {
      "page": "plot_cv_dent",
      "title": "Plot CV Density",
      "topics": [
        "plot_cv_dent"
      ]
    },
    {
      "page": "plot_int_boxplot",
      "title": "Plot Log-Intensity Boxplots by Sample",
      "topics": [
        "plot_int_boxplot"
      ]
    },
    {
      "page": "plot_missing_bar",
      "title": "Plot Missing Value Proportions by Sample or Variable",
      "topics": [
        "plot_missing_bar"
      ]
    },
    {
      "page": "plot_missing_heatmap",
      "title": "Plot Missing Value Heatmap",
      "topics": [
        "plot_missing_heatmap"
      ]
    },
    {
      "page": "plot_rank_abundance",
      "title": "Plot Rank Abundance",
      "topics": [
        "plot_rank_abundance"
      ]
    },
    {
      "page": "plot_rep_scatter",
      "title": "Plot Replicate Scatter Plots",
      "topics": [
        "plot_rep_scatter"
      ]
    },
    {
      "page": "plot_rle",
      "title": "Plot Relative Log Expression (RLE) Boxplots",
      "topics": [
        "plot_rle"
      ]
    },
    {
      "page": "plot_tic_bar",
      "title": "Plot Total Intensity by Sample",
      "topics": [
        "plot_tic_bar"
      ]
    },
    {
      "page": "remove_constant",
      "title": "Remove Constant Variables",
      "topics": [
        "remove_constant"
      ]
    },
    {
      "page": "remove_low_cv",
      "title": "Remove Variables with Low Coefficient of Variation",
      "topics": [
        "remove_low_cv"
      ]
    },
    {
      "page": "remove_low_expr",
      "title": "Remove Variables with Low Expression",
      "topics": [
        "remove_low_expr"
      ]
    },
    {
      "page": "remove_low_var",
      "title": "Remove Variables with Low Variance Remove Variables with Low Variance",
      "topics": [
        "remove_low_var"
      ]
    },
    {
      "page": "remove_rare",
      "title": "Remove Rare Variables with Too Many Missing Values",
      "topics": [
        "remove_rare"
      ]
    },
    {
      "page": "transform_alr",
      "title": "Additive Log-Ratio Transformation",
      "topics": [
        "transform_alr"
      ]
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        "Welcome to the Wild World of Data Preprocessing! 🧬",
        "Meet Our Star Player: Real Glycoproteomics Data 🌟",
        "The Magic Wand: One Function to Rule Them All ✨",
        "Still Like Magic, but With More Control?",
        "Taking the Scenic Route: Step-by-Step Preprocessing 🚶‍♀️",
        "Step 1: Normalization – Getting Everyone on the Same Page 📏",
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        "🎉 Mission Accomplished!",
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