{ "_id": "6ac4e741f511ae58c09a2e3d", "Package": "NADIA", "Type": "Package", "Title": "Missing Value-Aware Differential Abundance Analysis of DIA\nProteomics Data", "Version": "0.99.1", "Authors@R": "person(\ngiven = \"Sergio\",\nfamily = \"Ciordia\",\nemail = \"sciordia@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-5726-853X\"))", "Description": "Provides an end-to-end workflow for differential abundance\nanalysis of protein quantification data, with particular\nattention to missing values in data-independent acquisition\n(DIA) proteomics. Quantification reports exported from\nSpectronaut, DIA-NN and Proteome Discoverer for TMT and\nlabel-free experiments (DDA/DIA) are converted into a common\ndata structure, normalised, optionally batch-corrected, imputed\nand analysed using limma or limpa. The package includes\nindividual and two-stage imputation strategies that treat\nvalues assumed to be missing at random and missing not at\nrandom separately. Data-driven functions evaluate and rank\nnormalisation and imputation workflows using simulated\nmissingness or spike-in datasets with known ground truth,\nallowing method selection to be justified for each dataset.\nResults can be explored through interactive Highcharts\nvisualisations, static ggplot2 and ComplexHeatmap figures, and\nsortable tables.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "URL": "https://github.com/sciordia/NADIA,\nhttps://sciordia.github.io/NADIA/", "BugReports": "https://github.com/sciordia/NADIA/issues", "biocViews": "Software, Proteomics, MassSpectrometry,\nDifferentialExpression, Normalization, QualityControl,\nBatchEffect", "VignetteBuilder": "knitr", "Roxygen": "list(markdown = TRUE)", "Config/testthat/edition": "3", "Config/Needs/website": "pkgdown", "Config/roxygen2/version": "8.1.0", "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libuv1-dev\nlibxml2-dev libssl-dev libx11-dev zlib1g-dev", "Repository": "https://biocstaging.r-universe.dev", "Date/Publication": "2026-09-06 11:57:57 UTC", "RemoteUrl": "https://github.com/BiocStaging/NADIA", "RemoteRef": "HEAD", "RemoteSha": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-06 12:07:17 UTC", "User": "root" }, "Author": "Sergio Ciordia [aut, cre] (ORCID:\n)", "Maintainer": "Sergio Ciordia ", "_user": "biocstaging", "_type": "src", "_file": "NADIA_0.99.1.tar.gz", "_fileid": "https://r2.ropensci.org/3e6843af4d9da4633d7147d031a7ee7d44e51a0bb3e24fb8848deb6a0afc1414", "_filesize": 5787903, "_sha256": "3e6843af4d9da4633d7147d031a7ee7d44e51a0bb3e24fb8848deb6a0afc1414", "_expires": "2027-01-14T12:19:11.000Z", "_created": "2026-10-06T12:07:17.000Z", "_published": "2026-10-06T12:19:13.214Z", "_bioccheck": { "error": 0, "warning": 1, "note": 4 }, "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324", "_status": "success", "_upstream": "https://github.com/BiocStaging/NADIA", "_commit": { "id": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "author": "Sergio Ciordia ", "committer": "Sergio Ciordia ", "message": "fix: stop naming a parameter after a function we never call\n\nThe first Bioconductor build report raises \"NOTE: Avoid 'cat' and 'print'\noutside of 'show' methods\" against two lines of R/Benchmarking_Single.R. Neither\ncalls cat(). The name belonged to the argument of an anonymous function:\n\n function(cat, int) .blend_to_white(base_colors[cat], int)\n\nan abbreviation of the Category column it indexes. BiocCheck reads parsed code\nand cannot tell a local binding from the base function of the same name, so it\nreports the symbol wherever it appears.\n\nRenaming it to `category` removes the finding. That is worth more than being\nright about it: a reviewer who reads \"avoid cat()\" has to open the file and\nconvince themselves it is spurious, and that is time better spent on the parts\nof the package that need judgement. There are no cat() or print() calls anywhere\nin R/ -- the package reports through message(), and captures the output of the\ndependencies that do not.\n\nThe new name stays inside 80 columns, so it does not feed the separate NOTE\nabout line length.\n\nVerified: R CMD check Status: OK, and the cat/print NOTE is gone from BiocCheck,\nwhose remaining findings match the server's counts exactly (suppressWarnings 33,\nfunctions over 50 lines 106, long lines 1457, indents 13921). The next build\nreport should read 0 ERRORS | 1 WARNING | 4 NOTES.\n\nVersion bumped to 0.99.1: only a z bump triggers a rebuild, and the build runs\nfrom BiocStaging, not from this repository.\n\nCo-Authored-By: Claude Opus 5 (1M context) \nClaude-Session: https://claude.ai/code/session_01H1supa6pcoSpUBhFw6imvL\n", "time": 1788695877 }, "_maintainer": { "name": "Sergio Ciordia", "email": "sciordia@gmail.com", "login": "sciordia", "orcid": "0000-0002-5726-853X", "description": "Specialist Technician", "uuid": 26222135 }, "_distro": "resolute", "_jobs": [ { "job": 112260547584, "time": 226, "config": "bioc-checks", "r": "4.6.1", "check": "WARNING", "artifact": "11411288720" }, { "job": 112260547595, "time": 498, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11411484472" }, { "job": 112260547782, "time": 621, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11411249900" }, { "job": 112260547789, "time": 478, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11412878631" }, { "job": 112260547560, "time": 633, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11412979297" }, { "job": 112257533449, "time": 459, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11412922168" }, { "job": 112260547662, "time": 162, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11412417769" }, { "job": 112260547717, "time": 501, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11411274627" }, { "job": 112260547673, "time": 646, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11411444953" }, { "job": 112260547726, "time": 646, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11412224491" } ], "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.5.0", "role": "Depends" }, { "package": "dplyr", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "grDevices", "role": "Imports" }, { "package": "grid", "role": "Imports" }, { "package": "highcharter", "role": "Imports" }, { "package": "htmltools", "role": "Imports" }, { "package": "htmlwidgets", "role": "Imports" }, { "package": "jsonlite", "role": "Imports" }, { "package": "magrittr", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "paletteer", "role": "Imports" }, { "package": "RColorBrewer", "role": "Imports" }, { "package": "reactable", "role": "Imports" }, { "package": "readr", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "S4Vectors", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "stringr", "role": "Imports" }, { "package": "SummarizedExperiment", "role": "Imports" }, { "package": "tibble", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "tidyselect", "role": "Imports" }, { "package": "tools", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "arrow", "role": "Suggests" }, { "package": "BERT", "role": "Suggests" }, { "package": "Biobase", "role": "Suggests" }, { "package": "BiocStyle", "role": "Suggests" }, { "package": "circlize", "role": "Suggests" }, { "package": "cluster", "role": "Suggests" }, { "package": "ComplexHeatmap", "role": "Suggests" }, { "package": "crosstalk", "role": "Suggests" }, { "package": "DBI", "role": "Suggests" }, { "package": "duckdb", "role": "Suggests" }, { "package": "e1071", "role": "Suggests" }, { "package": "ggsci", "role": "Suggests" }, { "package": "impute", "role": "Suggests" }, { "package": "imputeLCMD", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "limma", "role": "Suggests" }, { "package": "limpa", "role": "Suggests" }, { "package": "lme4", "role": "Suggests" }, { "package": "MASS", "role": "Suggests" }, { "package": "Mfuzz", "role": "Suggests" }, { "package": "mice", "role": "Suggests" }, { "package": "missForest", "role": "Suggests" }, { "package": "norm", "role": "Suggests" }, { "package": "pcaMethods", "role": "Suggests" }, { "package": "pROC", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "rrcovNA", "role": "Suggests" }, { "package": "scales", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "tidyHeatmap", "role": "Suggests" }, { "package": "vegan", "role": "Suggests" }, { "package": "viridis", "role": "Suggests" }, { "package": "vsn", "role": "Suggests" }, { "package": "withr", "role": "Suggests" } ], "_owner": "biocstaging", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-51", "n": 8 }, { "week": "2025-52", "n": 12 }, { "week": "2026-01", "n": 10 }, { "week": "2026-02", "n": 64 }, { "week": "2026-03", "n": 6 }, { "week": "2026-04", "n": 1 }, { "week": "2026-05", "n": 7 }, { "week": "2026-06", "n": 2 }, { "week": "2026-07", "n": 19 }, { "week": "2026-08", "n": 15 }, { "week": "2026-09", "n": 15 }, { "week": "2026-10", "n": 28 }, { "week": "2026-11", "n": 14 }, { "week": "2026-12", "n": 29 }, { "week": "2026-13", "n": 28 }, { "week": "2026-14", "n": 8 }, { "week": "2026-15", "n": 11 }, { "week": "2026-17", "n": 7 }, { "week": "2026-18", "n": 18 }, { "week": "2026-21", "n": 1 }, { "week": "2026-22", "n": 2 }, { "week": "2026-24", "n": 5 }, { "week": "2026-28", "n": 4 }, { "week": "2026-31", "n": 32 }, { "week": "2026-32", "n": 9 }, { "week": "2026-33", "n": 19 }, { "week": "2026-34", "n": 12 }, { "week": "2026-35", "n": 6 }, { "week": "2026-36", "n": 24 } ], "_tags": [], "_topics": [ "software", "proteomics", "massspectrometry", "differentialexpression", "normalization", "qualitycontrol", "batcheffect" ], "_stars": 0, "_contributors": [ { "user": "sciordia", "count": 419, "uuid": 26222135 } ], "_userbio": { "uuid": 278472782, "type": "organization", "name": "BiocStaging", "followers": 2 }, "_downloads": { "count": 46, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/NADIA" }, "_mentions": 2, "_devurl": "https://github.com/sciordia/nadia", "_pkgdown": "https://sciordia.github.io/NADIA/", "_searchresults": 51, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NADIA.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md" ], "_cranurl": false, "_releases": [ { "version": "0.4.0", "date": "2020-11-23" }, { "version": "0.4.1", "date": "2021-01-06" }, { "version": "0.4.2", "date": "2022-10-02" } ], "_exports": [ "batch_correct_proteomics", "benchmark_auc_bars_gg", "benchmark_confusion_gg", "benchmark_confusion_overall_gg", "benchmark_heatmap_gg", "benchmark_metrics_bars_gg", "benchmark_roc_gg", "benchmark_signif_bars_gg", "benchmark_volcano_hc", "benchmark_volcano_hc_list", "benchmarking_multiple", "benchmarking_proteomics", "bm_compute_extended_ranking", "bm_compute_ranking", "bm_compute_ranking_by_comparison", "bm_plot_confusion_stacked", "bm_plot_extended_ranking_bars", "bm_plot_extended_ranking_heatmap", "bm_plot_metrics_comparison", "bm_plot_metrics_heatmap", "bm_plot_ranking_bars", "bm_plot_ranking_bars_by_comp", "bm_plot_ranking_heatmap", "bm_plot_ranking_heatmap_by_comp", "bm_plot_roc", "boxplot_highchart_list", "build_pca_scores", "cluster_centroids_highchart", "cluster_profile_highchart", "cluster_profile_highchart_list", "compute_benchmark_metrics", "compute_dispersion_metrics", "compute_opdea_metrics", "de_analysis_proteomics", "deps_with_clusters", "im_compute_metrics", "im_plot_acc_oi", "im_plot_metrics", "im_plot_nrmse", "im_plot_pss", "im_plot_ranking", "im_plot_sor", "im_prepare_se", "import_benchmark_metrics", "import_classified_results", "import_confusion_results", "import_imp_matrices", "import_norm_matrices", "import_opdea_results", "imputation_metrics", "impute_proteomics", "nadia_add_pattern_profiler", "nadia_connect", "nadia_deps_with_clusters", "nadia_export_parquet", "nadia_pattern_profiler", "nadia_preprocessing", "nadia_result", "nadia_skill_path", "nadia_tables", "nm_compute_metrics", "nm_plot_boxplot", "nm_plot_correlation", "nm_plot_density", "nm_plot_final_ranking", "nm_plot_mds", "nm_plot_mds1_ranking", "nm_plot_metrics", "nm_plot_pc1_ranking", "nm_plot_pca", "nm_plot_pcv", "nm_plot_pev", "nm_plot_pmad", "nm_plot_qq", "nm_plot_scatter", "nm_prepare_se", "nm_rank_cor", "nm_rank_final", "nm_rank_mds1", "nm_rank_pc1", "nm_rank_pcv", "nm_rank_pev", "nm_rank_pmad", "nm_run_normalizations", "normalization_metrics", "normalize_proteomics", "pattern_profiler_analysis", "pca_covariates_plot", "pca_highchart", "pca_highchart_list", "preprocess_diann", "preprocess_lfq", "preprocess_spectronaut", "preprocess_tmt", "process_proteomics", "protein_list_reactable", "protein_list_widget", "proteomics_heatmap", "proteomics_heatmap_list", "pvca_analysis", "pvca_compute", "pvca_plot", "quant_list_widget", "read_nadia", "read_pattern_profiler_data", "results_list_reactable", "results_list_widget", "summarize_pattern_profiler", "summary_list_widget", "volcano_highchart_list", "write_nadia" ], "_datasets": [ { "name": "nadia_dia", "title": "Example DIA experiment, already preprocessed", "object": "nadia_dia", "file": "nadia_dia.rda", "class": [ "spectronaut_data", "proteomics_data", "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "batch_correct_proteomics", "title": "Batch Correction with BERT", "topics": [ "batch_correct_proteomics" ] }, { "page": "benchmark_auc_bars_gg", "title": "AUC Bar Chart (ggplot2)", "topics": [ "benchmark_auc_bars_gg" ] }, { "page": "benchmark_confusion_gg", "title": "Confusion Matrix Heatmap (ggplot2)", "topics": [ "benchmark_confusion_gg" ] }, { "page": "benchmark_confusion_overall_gg", "title": "Overall Confusion Matrix Heatmap (ggplot2)", "topics": [ "benchmark_confusion_overall_gg" ] }, { "page": "benchmark_heatmap_gg", "title": "Performance Heatmap (ggplot2)", "topics": [ "benchmark_heatmap_gg" ] }, { "page": "benchmark_metrics_bars_gg", "title": "Grouped Metrics Bar Chart (ggplot2)", "topics": [ "benchmark_metrics_bars_gg" ] }, { "page": "benchmark_roc_gg", "title": "ROC Curves by Comparison (ggplot2)", "topics": [ "benchmark_roc_gg" ] }, { "page": "benchmark_signif_bars_gg", "title": "Significant Proteins Stacked Bars (ggplot2)", "topics": [ "benchmark_signif_bars_gg" ] }, { "page": "benchmark_volcano_hc", "title": "Benchmark Volcano Plot (Highcharter)", "topics": [ "benchmark_volcano_hc" ] }, { "page": "benchmark_volcano_hc_list", "title": "List of Benchmark Volcano Plots (Highcharter)", "topics": [ "benchmark_volcano_hc_list" ] }, { "page": "benchmarking_multiple", "title": "Multiple-method OpDEA Benchmarking", "topics": [ "benchmarking_multiple" ] }, { "page": "benchmarking_proteomics", "title": "Benchmark Proteomics Differential Expression Results", "topics": [ "benchmarking_proteomics" ] }, { "page": "bm_compute_extended_ranking", "title": "Compute extended ranking across 11 classification + OpDEA metrics", "topics": [ "bm_compute_extended_ranking" ] }, { "page": "bm_compute_ranking", "title": "Compute OpDEA ranking across multiple methods", "topics": [ "bm_compute_ranking" ] }, { "page": "bm_compute_ranking_by_comparison", "title": "Compute OpDEA ranking separately for each comparison", "topics": [ "bm_compute_ranking_by_comparison" ] }, { "page": "bm_plot_confusion_stacked", "title": "Stacked bar chart of TP/FP/FN/TN (OpDEA Figure 5 style)", "topics": [ "bm_plot_confusion_stacked" ] }, { "page": "bm_plot_extended_ranking_bars", "title": "Horizontal bar chart of extended combined ranking", "topics": [ "bm_plot_extended_ranking_bars" ] }, { "page": "bm_plot_extended_ranking_heatmap", "title": "Heatmap of extended ranking (11 metrics)", "topics": [ "bm_plot_extended_ranking_heatmap" ] }, { "page": "bm_plot_metrics_comparison", "title": "Boxplot comparison of metric distributions across methods", "topics": [ "bm_plot_metrics_comparison" ] }, { "page": "bm_plot_metrics_heatmap", "title": "Heatmap of aggregated metric values (not ranks)", "topics": [ "bm_plot_metrics_heatmap" ] }, { "page": "bm_plot_ranking_bars", "title": "Bar chart of final ranks", "topics": [ "bm_plot_ranking_bars" ] }, { "page": "bm_plot_ranking_bars_by_comp", "title": "Bar chart of final ranks for a single comparison", "topics": [ "bm_plot_ranking_bars_by_comp" ] }, { "page": "bm_plot_ranking_heatmap", "title": "Heatmap of metric ranks by method", "topics": [ "bm_plot_ranking_heatmap" ] }, { "page": "bm_plot_ranking_heatmap_by_comp", "title": "Heatmap of metric ranks for a single comparison", "topics": [ "bm_plot_ranking_heatmap_by_comp" ] }, { "page": "bm_plot_roc", "title": "ROC Curves by Method for a Single Comparison", "topics": [ "bm_plot_roc" ] }, { "page": "boxplot_highchart_list", "title": "Interactive Highcharts Boxplot for Proteomics", "topics": [ "boxplot_highchart_list" ] }, { "page": "build_clustering_matrix", "title": "Build the clustering matrix aggregated by condition", "topics": [ "build_clustering_matrix" ] }, { "page": "build_long_output", "title": "Build the output table in LONG format", "topics": [ "build_long_output" ] }, { "page": "build_pca_scores", "title": "Build a PCA scores data frame from data in long format", "topics": [ "build_pca_scores" ] }, { "page": "cluster_centroids_highchart", "title": "Centroid plot for all the clusters", "topics": [ "cluster_centroids_highchart" ] }, { "page": "cluster_profile_highchart", "title": "Cluster profile plot with Highcharts", "topics": [ "cluster_profile_highchart" ] }, { "page": "cluster_profile_highchart_list", "title": "List of cluster profile plots with Highcharts", "topics": [ "cluster_profile_highchart_list" ] }, { "page": "compute_benchmark_metrics", "title": "Compute benchmark metrics for all comparisons", "topics": [ "compute_benchmark_metrics" ] }, { "page": "compute_confidence_ellipse", "title": "Compute the confidence ellipse per group", "topics": [ "compute_confidence_ellipse" ] }, { "page": "compute_dispersion_metrics", "title": "Compute dispersion metrics by Comparison x Species", "topics": [ "compute_dispersion_metrics" ] }, { "page": "compute_hulls", "title": "Compute the convex hull (enclosing polygon) per group", "topics": [ "compute_hulls" ] }, { "page": "compute_opdea_metrics", "title": "Compute OpDEA metrics for all comparisons", "topics": [ "compute_opdea_metrics" ] }, { "page": "configure_cluster_palette", "title": "Configure the colour palette for the clusters", "topics": [ "configure_cluster_palette" ] }, { "page": "create_expression_set", "title": "Create an ExpressionSet for Mfuzz", "topics": [ "create_expression_set" ] }, { "page": "de_analysis_proteomics", "title": "Perform differential expression analysis on proteomics data", "topics": [ "de_analysis_proteomics" ] }, { "page": "deps_with_clusters", "title": "Differential abundance with the Pattern Profiler cluster of each protein", "topics": [ "deps_with_clusters" ] }, { "page": "detect_condition_columns", "title": "Detect the condition columns (z-scores)", "topics": [ "detect_condition_columns" ] }, { "page": "evaluate_cluster_range", "title": "Evaluate a range of cluster numbers", "topics": [ "evaluate_cluster_range" ] }, { "page": "extract_se_data", "title": "Extract data from a SummarizedExperiment", "topics": [ "extract_se_data" ] }, { "page": "filter_significant_features", "title": "Filter features by significance", "topics": [ "filter_significant_features" ] }, { "page": "get_annotation_palette", "title": "Build the Colour Palette for Categorical Annotations", "topics": [ "get_annotation_palette" ] }, { "page": "get_heatmap_palette", "title": "Build the Colour Palette for the Heatmap Values", "topics": [ "get_heatmap_palette" ] }, { "page": "im_compute_metrics", "title": "Compute imputation quality metrics (NRMSE, SOR, PSS, ACC_OI)", "topics": [ "im_compute_metrics" ] }, { "page": "im_plot_acc_oi", "title": "ACC_OI bar plot per imputation method", "topics": [ "im_plot_acc_oi" ] }, { "page": "im_plot_metrics", "title": "Faceted bar chart of all 4 imputation quality metrics", "topics": [ "im_plot_metrics" ] }, { "page": "im_plot_nrmse", "title": "NRMSE bar plot per imputation method", "topics": [ "im_plot_nrmse" ] }, { "page": "im_plot_pss", "title": "PSS bar plot per imputation method", "topics": [ "im_plot_pss" ] }, { "page": "im_plot_ranking", "title": "Ranking heatmap of imputation methods", "topics": [ "im_plot_ranking" ] }, { "page": "im_plot_sor", "title": "SOR bar plot per imputation method", "topics": [ "im_plot_sor" ] }, { "page": "im_prepare_se", "title": "Build a SummarizedExperiment for imputation benchmarking", "topics": [ "im_prepare_se" ] }, { "page": "import_benchmark_metrics", "title": "Import benchmark metrics from multiple benchmark result folders", "topics": [ "import_benchmark_metrics" ] }, { "page": "import_classified_results", "title": "Import classified results from multiple benchmark result folders", "topics": [ "import_classified_results" ] }, { "page": "import_confusion_results", "title": "Import confusion matrices from multiple benchmark result folders", "topics": [ "import_confusion_results" ] }, { "page": "import_imp_matrices", "title": "Import imputed matrices into a SummarizedExperiment", "topics": [ "import_imp_matrices" ] }, { "page": "import_norm_matrices", "title": "Import normalized matrices into a SummarizedExperiment", "topics": [ "import_norm_matrices" ] }, { "page": "import_opdea_results", "title": "Import OpDEA metrics from multiple benchmark result folders", "topics": [ "import_opdea_results" ] }, { "page": "imputation_metrics", "title": "Generate imputation quality metric plots and ranking", "topics": [ "imputation_metrics" ] }, { "page": "impute_proteomics", "title": "Impute proteomics data", "topics": [ "impute_proteomics" ] }, { "page": "merge_significance_info", "title": "Merge significance information from DEPs_results", "topics": [ "merge_significance_info" ] }, { "page": "nadia_add_pattern_profiler", "title": "Add a Pattern Profiler run to an existing '.nadia' file", "topics": [ "nadia_add_pattern_profiler" ] }, { "page": "nadia_connect", "title": "Open a connection to a '.nadia' file", "topics": [ "nadia_connect" ] }, { "page": "nadia_deps_with_clusters", "title": "Differential abundance with clusters, from a '.nadia' file", "topics": [ "nadia_deps_with_clusters" ] }, { "page": "nadia_dia", "title": "Example DIA experiment, already preprocessed", "topics": [ "nadia_dia" ] }, { "page": "nadia_export_parquet", "title": "Export the tables of a '.nadia' file to Parquet", "topics": [ "nadia_export_parquet" ] }, { "page": "nadia_pattern_profiler", "title": "Rebuild the Pattern Profiler table from a '.nadia' file", "topics": [ "nadia_pattern_profiler" ] }, { "page": "nadia_preprocessing", "title": "Rebuild the preprocessing object from a '.nadia' file", "topics": [ "nadia_preprocessing" ] }, { "page": "nadia_result", "title": "Rebuild the processing result from a '.nadia' file", "topics": [ "nadia_result" ] }, { "page": "nadia_skill_path", "title": "Locate the NADIA agent skill", "topics": [ "nadia_skill_path" ] }, { "page": "nadia_tables", "title": "List the contents of a '.nadia' file without loading it", "topics": [ "nadia_tables" ] }, { "page": "nm_compute_metrics", "title": "Compute quantitative group-separation metrics per normalization method", "topics": [ "nm_compute_metrics" ] }, { "page": "nm_plot_boxplot", "title": "Intensity boxplot per method", "topics": [ "nm_plot_boxplot" ] }, { "page": "nm_plot_correlation", "title": "Intra-group correlation boxplot per method (PRONE-style)", "topics": [ "nm_plot_correlation" ] }, { "page": "nm_plot_density", "title": "Density plot per method", "topics": [ "nm_plot_density" ] }, { "page": "nm_plot_final_ranking", "title": "Horizontal bar chart of combined final ranking", "topics": [ "nm_plot_final_ranking" ] }, { "page": "nm_plot_mds", "title": "MDS 2D scatter per method", "topics": [ "nm_plot_mds" ] }, { "page": "nm_plot_mds1_ranking", "title": "Horizontal bar chart of MDS1 variance ranking", "topics": [ "nm_plot_mds1_ranking" ] }, { "page": "nm_plot_metrics", "title": "Bar chart of group-separation metrics per normalization method", "topics": [ "nm_plot_metrics" ] }, { "page": "nm_plot_pc1_ranking", "title": "Horizontal bar chart of PC1 variance ranking", "topics": [ "nm_plot_pc1_ranking" ] }, { "page": "nm_plot_pca", "title": "PCA scatter plot per method", "topics": [ "nm_plot_pca" ] }, { "page": "nm_plot_pcv", "title": "PCV boxplot per method (PRONE-style)", "topics": [ "nm_plot_pcv" ] }, { "page": "nm_plot_pev", "title": "PEV boxplot per method (PRONE-style)", "topics": [ "nm_plot_pev" ] }, { "page": "nm_plot_pmad", "title": "PMAD boxplot per method (PRONE-style)", "topics": [ "nm_plot_pmad" ] }, { "page": "nm_plot_qq", "title": "Q-Q plot per method (NormalyzerDE style)", "topics": [ "nm_plot_qq" ] }, { "page": "nm_plot_scatter", "title": "Sample-vs-sample scatter plot per method (NormalyzerDE style)", "topics": [ "nm_plot_scatter" ] }, { "page": "nm_prepare_se", "title": "Prepare a SummarizedExperiment from a proteomics_data object", "topics": [ "nm_prepare_se" ] }, { "page": "nm_rank_cor", "title": "Rank normalization methods by median intragroup correlation (descending - higher is better)", "topics": [ "nm_rank_cor" ] }, { "page": "nm_rank_final", "title": "Compute a combined final ranking across PCV, PMAD, PEV, Correlation and group-separation (PC1 F-ratio)", "topics": [ "nm_rank_final" ] }, { "page": "nm_rank_mds1", "title": "Rank normalization methods by MDS1 variance explained", "topics": [ "nm_rank_mds1" ] }, { "page": "nm_rank_pc1", "title": "Rank normalization methods by PC1 variance explained", "topics": [ "nm_rank_pc1" ] }, { "page": "nm_rank_pcv", "title": "Rank normalization methods by median PCV (ascending - lower is better)", "topics": [ "nm_rank_pcv" ] }, { "page": "nm_rank_pev", "title": "Rank normalization methods by median PEV (ascending - lower is better)", "topics": [ "nm_rank_pev" ] }, { "page": "nm_rank_pmad", "title": "Rank normalization methods by median PMAD (ascending - lower is better)", "topics": [ "nm_rank_pmad" ] }, { "page": "nm_run_normalizations", "title": "Run multiple normalization methods from a baseline assay", "topics": [ "nm_run_normalizations" ] }, { "page": "normalization_metrics", "title": "Generate quality metric plots for normalization comparison", "topics": [ "normalization_metrics" ] }, { "page": "normalize_proteomics", "title": "Normalize proteomics data", "topics": [ "normalize_proteomics" ] }, { "page": "pattern_profiler_analysis", "title": "Pattern Profiler Analysis", "topics": [ "pattern_profiler_analysis" ] }, { "page": "pca_covariates_plot", "title": "PCA Plots Colored by Covariates", "topics": [ "pca_covariates_plot" ] }, { "page": "pca_highchart", "title": "Interactive PCA Plot with Highcharts", "topics": [ "pca_highchart" ] }, { "page": "pca_highchart_list", "title": "Build a List of PCA Plots for Multiple Subsets", "topics": [ "pca_highchart_list" ] }, { "page": "prepare_heatmap_data", "title": "Prepare Long-Format Data for tidyHeatmap", "topics": [ "prepare_heatmap_data" ] }, { "page": "preprocess_diann", "title": "Preprocess DIA-NN protein-group matrices", "topics": [ "preprocess_diann" ] }, { "page": "preprocess_lfq", "title": "Preprocess Proteome Discoverer LFQ exports", "topics": [ "preprocess_lfq" ] }, { "page": "preprocess_spectronaut", "title": "Preprocess Spectronaut reports", "topics": [ "preprocess_spectronaut" ] }, { "page": "preprocess_tmt", "title": "Preprocess Proteome Discoverer TMT exports", "topics": [ "preprocess_tmt" ] }, { "page": "print.diann_data", "title": "Print a summary of a DIA-NN preprocessing result", "topics": [ "print.diann_data" ] }, { "page": "print.lfq_data", "title": "Print a summary of an LFQ preprocessing result", "topics": [ "print.lfq_data" ] }, { "page": "print.nadia_db", "title": "Print a summary of a '.nadia' file", "topics": [ "print.nadia_db" ] }, { "page": "print.proteomics_heatmap", "title": "Draw a proteomics heatmap", "topics": [ "print.proteomics_heatmap" ] }, { "page": "print.proteomics_result", "title": "Print method for proteomics_result", "topics": [ "print.proteomics_result" ] }, { "page": "print.spectronaut_data", "title": "Print a summary of a Spectronaut preprocessing result", "topics": [ "print.spectronaut_data" ] }, { "page": "print.tmt_data", "title": "Print a summary of a TMT preprocessing result", "topics": [ "print.tmt_data" ] }, { "page": "process_proteomics", "title": "Process proteomics data", "topics": [ "process_proteomics" ] }, { "page": "protein_list_reactable", "title": "Interactive Reactable Table for Protein_ID Data (post-Spectronaut)", "topics": [ "protein_list_reactable" ] }, { "page": "protein_list_widget", "title": "Full Widget for the Protein_ID Table with Filters, Search and Excel Export", "topics": [ "protein_list_widget" ] }, { "page": "proteomics_heatmap", "title": "Create a tidyHeatmap Heatmap for Proteomics", "topics": [ "proteomics_heatmap" ] }, { "page": "proteomics_heatmap_list", "title": "Build a List of Heatmaps for Several Subsets", "topics": [ "proteomics_heatmap_list" ] }, { "page": "pvca_analysis", "title": "PVCA Analysis - Orchestrator", "topics": [ "pvca_analysis" ] }, { "page": "pvca_compute", "title": "Compute PVCA variance components", "topics": [ "pvca_compute" ] }, { "page": "pvca_plot", "title": "Plot PVCA variance components", "topics": [ "pvca_plot" ] }, { "page": "quant_list_widget", "title": "Full Widget for the Protein_QUANT Table with the log2 Matrix Appended", "topics": [ "quant_list_widget" ] }, { "page": "read_nadia", "title": "Read a '.nadia' file", "topics": [ "read_nadia" ] }, { "page": "read_pattern_profiler_data", "title": "Read Pattern Profiler data from a parquet file", "topics": [ "read_pattern_profiler_data" ] }, { "page": "results_list_reactable", "title": "Interactive Reactable Table for Differential Expression Results", "topics": [ "results_list_reactable" ] }, { "page": "results_list_widget", "title": "Full Widget with Filters, Search, Export and CSS", "topics": [ "results_list_widget" ] }, { "page": "run_mfuzz_clustering", "title": "Run Mfuzz clustering", "topics": [ "run_mfuzz_clustering" ] }, { "page": "select_optimal_clusters", "title": "Select the optimal number of clusters", "topics": [ "select_optimal_clusters" ] }, { "page": "standardize_eset", "title": "Standardise an ExpressionSet (row-wise z-score)", "topics": [ "standardize_eset" ] }, { "page": "summarize_pattern_profiler", "title": "Summary of the Pattern Profiler data", "topics": [ "summarize_pattern_profiler" ] }, { "page": "summary_list_widget", "title": "Interactive Reactable Table for the Sample Metadata", "topics": [ "summary_list_widget" ] }, { "page": "volcano_highchart_list", "title": "Interactive Volcano Plot with Highcharter", "topics": [ "volcano_highchart_list" ] }, { "page": "wrap_heatmap_with_title", "title": "Wrap a Heatmap Together With Its Title", "topics": [ "wrap_heatmap_with_title" ] }, { "page": "write_nadia", "title": "Write a complete analysis to a single '.nadia' file", "topics": [ "write_nadia" ] } ], "_pkglogo": "https://github.com/BiocStaging/NADIA/raw/HEAD/man/figures/logo.svg", "_readme": "https://github.com/BiocStaging/NADIA/raw/HEAD/README.md", "_rundeps": [ "abind", "assertthat", "backports", "base64enc", "Biobase", "BiocGenerics", "bit", "bit64", "broom", "bslib", "cachem", "cli", "clipr", "cpp11", "crayon", "curl", "data.table", "DelayedArray", "digest", "dplyr", "evaluate", "farver", "fastmap", "fontawesome", "fs", "generics", "GenomicRanges", "ggplot2", "glue", "gtable", "highcharter", "highr", "hms", "htmltools", "htmlwidgets", "igraph", "IRanges", "isoband", "jquerylib", "jsonlite", "knitr", "labeling", "lattice", "lifecycle", "lubridate", "magrittr", "Matrix", "MatrixGenerics", "matrixStats", "memoise", "mime", "paletteer", "pillar", "pkgconfig", "prettyunits", "prismatic", "progress", "purrr", "quantmod", "R6", "rappdirs", "RColorBrewer", "reactable", "reactR", "readr", "rematch2", "rjson", "rlang", "rlist", "rmarkdown", "rstudioapi", "S4Arrays", "S4Vectors", "S7", "sass", "scales", "Seqinfo", "SparseArray", "stringi", "stringr", "SummarizedExperiment", "tibble", "tidyr", "tidyselect", "timechange", "tinytex", "TTR", "tzdb", "utf8", "vctrs", "viridisLite", "vroom", "withr", "xfun", "XML", "xts", "XVector", "yaml", "zoo" ], "_vignettes": [ { "source": "NADIA.Rmd", "filename": "NADIA.html", "title": "An introduction to NADIA", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Installation", "Example data", "How missing values are represented", "Filtering, log2 transformation and normalisation", "Imputation of missing values", "The workflow in a single call", "Where the processed data are stored", "Differential abundance results", "Relationship with the missing values", "Detection and non-detection patterns between conditions", "Visualising the results", "Interactive figures", "Static figure", "Next steps", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 16 }, { "source": "batch-correction.Rmd", "filename": "batch-correction.html", "title": "Batch correction: diagnose, correct, verify", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Installation", "The sample annotation", "A simulated batch effect", "Step 1: is the design suitable for batch correction?", "Step 2: how much variance does the batch explain?", "Why the default hides it, and what to do", "Step 3: correct, and keep the biology", "Protecting a variable inside ComBat", "Step 4: verify", "Did the batch effect go?", "Did the biology survive?", "What it changed in the results", "Removing two factors, one after the other", "Inspecting the correction with PCA", "Applying the workflow to a real batch effect", "The batch has to be declared, not discovered", "The decomposition finds it", "Correcting it, and checking against biology", "Visual assessment with PCA", "Statistical significance and fold-change magnitude", "References", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:18:49", "commits": 12 }, { "source": "benchmarking.Rmd", "filename": "benchmarking.html", "title": "Benchmarking with a spike-in: scoring against known truth", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Installation", "The experiment", "Declaring the truth", "Scoring a pipeline", "The metrics_table summary", "How TP, FP, TN and FN are defined", "The confusion plots: the whole picture at once", "Species-level confusion plot", "Overall confusion plot", "The metrics heatmap", "The OpDEA metrics", "Interpreting ROC curves", "The full ROC curve", "Zooming into the low-FPR region", "Comparing search engines across FPR ranges", "Volcano plots as diagnostic tools", "Comparing multiple pipelines", "Comparing TP, FP, TN and FN", "Ranking pipelines with the OpDEA criteria", "Comparing saved results and external pipelines", "What this benchmark can and cannot show", "References", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 9 }, { "source": "choosing-methods.Rmd", "filename": "choosing-methods.html", "title": "Choosing normalisation and imputation methods", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Installation and packages", "Normalisation", "What normalisation does", "Normalisation methods available in NADIA", "How normalisation methods are evaluated", "Comparing normalisation methods with NADIA", "Imputation", "Why values are missing", "How NADIA represents missing intensities", "Imputation methods available in NADIA", "How imputation methods are evaluated", "Comparing imputation methods with NADIA", "Applying the selected combination", "Effect on differential abundance results", "Practical decision guide", "References and software", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 10 }, { "source": "input-formats.Rmd", "filename": "input-formats.html", "title": "Input formats: Spectronaut, DIA-NN, TMT and LFQ", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "DIA: Spectronaut", "DIA: DIA-NN", "Declaring the experimental design", "TMT: Proteome Discoverer", "Label-free: Proteome Discoverer", "Where the design comes from", "Naming the conditions", "Four sources, one common object", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 8 }, { "source": "missing-values.Rmd", "filename": "missing-values.html", "title": "Missing values: what they mean and how to fill them", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Installation", "Why values are missing", "How NADIA represents missing intensities", "Diagnosing missingness in the example data", "Data processing shapes the missing-value pattern", "Imputation strategies available in NADIA", "Why one method may not represent every gap", "The default hybrid: combo", "softHybrid: a continuous combination", "limpa: detection-aware estimates with uncertainty", "Choosing among the strategies", "References and software", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 7 }, { "source": "pattern-profiler.Rmd", "filename": "pattern-profiler.html", "title": "Pattern Profiler: identifying shared protein profiles", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Setup and example data", "Running Pattern Profiler", "Selecting proteins for clustering", "Choosing the number of clusters", "Understanding the soft-clustering output", "Visualising the expression patterns", "Protein profiles within each cluster", "Comparing cluster centroids", "Saving and reusing the results", "Saving the long-format table as Parquet", "Storing Pattern Profiler in a NADIA project", "Practical recommendations", "References", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 6 }, { "source": "results-and-export.Rmd", "filename": "results-and-export.html", "title": "Results and export: sharing and preserving an analysis", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Prepare an example analysis", "Install and load NADIA", "Run the processing workflow", "Choose an output for the task", "Export tabular results", "Choose between TSV and Parquet", "Create a set of TSV and/or Parquet files", "Archive a complete analysis", "Write and read a .nadia file", "Restore and verify the result", "Inspect stored tables and provenance", "Query or extract the archive", "Combine differential abundance with clustering", "Explore results with interactive tables", "Save interactive HTML", "Save a complete widget page", "Save an individual widget as one file", "Preserve reproducibility", "References", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 6 }, { "source": "visualization.Rmd", "filename": "visualization.html", "title": "Visualisation: exploring and presenting results", "author": "Sergio Ciordia", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Setup and example data", "Installation", "Processing the example dataset", "Choosing the appropriate visualisation", "Interactive and static output", "Highcharts licence", "Volcano plots", "Summarising the selected comparison", "Creating and reading the plot", "Labelling selected proteins and multiple comparisons", "Boxplots of sample distributions", "Comparing assays numerically", "Creating and reading the boxplot", "Principal component analysis", "Comparing protein subsets", "Creating and reading the PCA plot", "Subset modes, ellipses, and sample filtering", "Heatmaps", "Selecting proteins for the heatmap", "Creating and reading a focused heatmap", "Annotations and repeated heatmaps", "Protein pattern clusters", "Building and summarising the example clusters", "Comparing cluster centroids", "Inspecting representative protein profiles", "Colours and consistent presentation", "Exporting figures and data", "Interactive charts", "Static heatmaps", "Practical recommendations", "Session information" ], "created": "2026-07-30 20:37:35", "modified": "2026-09-05 08:00:32", "commits": 7 } ], "_score": 6.1242106834362176, "_indexed": true, "_nocasepkg": "nadia", "_universes": [ "biocstaging", "sciordia" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.99.1", "date": "2026-10-06T12:10:28.000Z", "distro": "resolute", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/0f8ab6a6eb95eda1b4e7734212fbfe76e7af104e2b00068f60c472aa7c926847", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" }, { "r": "4.6.1", "os": "linux", "version": "0.99.1", "date": "2026-10-06T12:10:49.000Z", "distro": "resolute", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/eab73741bfd8a71466b1246b691cb0dc90a81043063a728b65503c2cbc65cf60", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" }, { "r": "4.5.3", "os": "mac", "version": "0.99.1", "date": "2026-10-06T12:09:24.000Z", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/37022a3ef9c03ead4d7d0e8731a92b87326d2a5c17fc0c06537d0d7eec50e3f3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" }, { "r": "4.6.1", "os": "mac", "version": "0.99.1", "date": "2026-10-06T12:09:48.000Z", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/cd8728acd246327ae1095105b7b23c5c27b32c544ab1312ded694617c787e751", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" }, { "r": "4.6.0", "os": "wasm", "version": "0.99.1", "date": "2026-10-06T12:10:34.000Z", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/a247c66d341c0b45069342a05c9192faa77c8abdee07985058f8d61b055566d5", "status": "success", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" }, { "r": "4.7.0", "os": "win", "version": "0.99.1", "date": "2026-10-06T12:10:21.000Z", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/3035f46987b55c75accc46ea93ea2f7898b410ae1f2fb031dc607d8ce069055d", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" }, { "r": "4.5.3", "os": "win", "version": "0.99.1", "date": "2026-10-06T12:09:16.000Z", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/5bbd7abfe376beedd207337df86715e2cad8751cea82f0c25628e310620c1ac2", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" }, { "r": "4.6.1", "os": "win", "version": "0.99.1", "date": "2026-10-06T12:09:19.000Z", "commit": "c4a896085c0e2b7966e6ddf55af3f07aa3a4c114", "fileid": "https://r2.ropensci.org/750e70d2a88d9161305da120a78a7db07289e0548adc2194154b15225ca172d1", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37460144324" } ] }