{ "_id": "6a297fe5732311cd875b255c", "Package": "metamorphr", "Title": "Tidy and Streamlined Metabolomics Data Workflows", "Version": "0.4.1", "Authors@R": "person(\"Yannik\", \"Schermer\", , \"yannik.schermer@chem.rptu.de\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0009-0002-5201-057X\"))", "Description": "Facilitate tasks typically encountered during metabolomics\ndata analysis including data import, filtering, missing value\nimputation (Stacklies et al. (2007)\n, Stekhoven et al. (2012)\n, Tibshirani et al. (2017)\n, Troyanskaya et al. (2001)\n), normalization (Bolstad\net al. (2003) , Dieterle\net al. (2006) , Zhao et al. (2020)\n) transformation, centering and\nscaling (Van Den Berg et al. (2006)\n) as well as statistical tests and\nplotting. 'metamorphr' introduces a tidy (Wickham et al. (2019)\n) format for metabolomics data and is\ndesigned to make it easier to build elaborate analysis\nworkflows and to integrate them with 'tidyverse' packages\nincluding 'dplyr' and 'ggplot2'.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "LazyData": "true", "Config/testthat/edition": "3", "URL": "https://github.com/yasche/metamorphr,\nhttps://yasche.github.io/metamorphr/", "BugReports": "https://github.com/yasche/metamorphr/issues", "VignetteBuilder": "knitr", "Config/roxygen2/version": "8.0.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-10 15:12:16 UTC", "User": "root" }, "Author": "Yannik Schermer [aut, cre, cph] (ORCID:\n)", "Maintainer": "Yannik Schermer ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-06-10 12:40:08 UTC", "RemoteUrl": "https://github.com/cran/metamorphr", "RemoteRef": "HEAD", "RemoteSha": "594805f524158e5996dcfc15421ae6b87d89b125", "MD5sum": "57215e50e9d323cd84b547e79a2129f1", "_user": "cran", "_type": "src", "_file": "metamorphr_0.4.1.tar.gz", "_fileid": "455d0db0a5ff2de4fe515d44a24ebc6eec7be254f1e5b15611d35de242a0c5b2", "_filesize": 1276252, "_sha256": "455d0db0a5ff2de4fe515d44a24ebc6eec7be254f1e5b15611d35de242a0c5b2", "_created": "2026-06-10T15:12:16.000Z", "_published": "2026-06-10T15:16:53.739Z", "_distro": "noble", "_jobs": [ { "job": 80593856056, "time": 190, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7540005090" }, { "job": 80593855984, "time": 224, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7540019711" }, { "job": 80592822229, "time": 303, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7539923237" }, { "job": 80593855965, "time": 164, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7539993420" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/27285854949", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/metamorphr", "_commit": { "id": "594805f524158e5996dcfc15421ae6b87d89b125", "author": "Yannik Schermer ", "committer": "cran-robot ", "message": "version 0.4.1\n", "time": 1781095208 }, "_maintainer": { "name": "Yannik Schermer", "email": "yannik.schermer@chem.rptu.de" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5", "role": "Depends" }, { "package": "broom", "role": "Imports" }, { "package": "crayon", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "impute", "role": "Imports" }, { "package": "lifecycle", "role": "Imports" }, { "package": "magrittr", "role": "Imports" }, { "package": "missForest", "role": "Imports" }, { "package": "pcaMethods", "role": "Imports" }, { "package": "purrr", "role": "Imports" }, { "package": "readr", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "stringi", "role": "Imports" }, { "package": "tibble", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "vctrs", "role": "Imports" }, { "package": "withr", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "qsmooth", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "stringr", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2025-36", "n": 1 }, { "week": "2025-41", "n": 1 }, { "week": "2026-10", "n": 1 }, { "week": "2026-24", "n": 2 } ], "_tags": [ { "name": "0.1.1", "date": "2025-09-01" }, { "name": "0.2.0", "date": "2025-10-09" }, { "name": "0.3.0", "date": "2026-03-04" }, { "name": "0.4.0", "date": "2026-06-09" }, { "name": "0.4.1", "date": "2026-06-10" } ], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 170, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/metamorphr" }, "_devurl": "https://github.com/yasche/metamorphr", "_pkgdown": "https://yasche.github.io/metamorphr/", "_searchresults": 5, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/metamorphr.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/yasche/metamorphr", "_realowner": "yasche", "_cranurl": false, "_releases": [ { "version": "0.1.1", "date": "2025-09-01" }, { "version": "0.2.0", "date": "2025-10-09" }, { "version": "0.3.0", "date": "2026-03-04" }, { "version": "0.4.0", "date": "2026-06-09" }, { "version": "0.4.1", "date": "2026-06-10" } ], "_exports": [ "%>%", "calc_km", "calc_kmd", "calc_neutral_loss", "calc_nominal_km", "collapse_max", "collapse_mean", "collapse_median", "collapse_min", "convert_from_matrix", "convert_from_wide", "create_metadata_skeleton", "filter_blank", "filter_cv", "filter_global_mv", "filter_grouped_mv", "filter_msn", "filter_mz", "filter_neutral_loss", "formula_to_mass", "impute_bpca", "impute_global_lowest", "impute_knn", "impute_lls", "impute_lod", "impute_mean", "impute_median", "impute_min", "impute_nipals", "impute_ppca", "impute_rf", "impute_svd", "impute_user_value", "join_metadata", "msn_calc_nl", "msn_scale", "normalize_cyclic_loess", "normalize_factor", "normalize_median", "normalize_pqn", "normalize_quantile_all", "normalize_quantile_batch", "normalize_quantile_group", "normalize_quantile_smooth", "normalize_ref", "normalize_sum", "plot_pca", "plot_volcano", "read_featuretable", "read_featuretable_mzmine", "read_mgf", "remove_empty_cols", "scale_auto", "scale_center", "scale_level", "scale_pareto", "scale_range", "scale_vast", "scale_vast_grouped", "summary_featuretable", "transform_log", "transform_power" ], "_datasets": [ { "name": "atoms", "title": "A tibble containing the NIST standard atomic weights", "object": "atoms", "class": [ "tbl_df", "tbl", "data.frame" ], "fields": [ "Number", "Element", "Isotope", "Symbol", "Weight", "Composition", "Standard_Weight" ], "rows": 442, "table": true, "tojson": true }, { "name": "toy_metaboscape", "title": "A small toy data set created from a feature table in MetaboScape style", "object": "toy_metaboscape", "class": [ "tbl_df", "tbl", "data.frame" ], "fields": [ "UID", "Feature", "Sample", "Intensity", "RT", "m/z", "Name", "Formula" ], "rows": 110, "table": true, "tojson": true }, { "name": "toy_metaboscape_metadata", "title": "Sample metadata for the fictional dataset 'toy_metaboscape'", "object": "toy_metaboscape_metadata", "class": [ "tbl_df", "tbl", "data.frame" ], "fields": [ "Sample", "Group", "Replicate", "Batch", "Factor" ], "rows": 11, "table": true, "tojson": true }, { "name": "toy_mgf", "title": "A small toy data set containing MSn spectra", "object": "toy_mgf", "class": [ "tbl_df", "tbl", "data.frame" ], "fields": [ "VARIABLEONE", "VARIABLETWO", "VARIABLETHREE", "PEPMASS", "MSn" ], "rows": 3, "table": false, "tojson": true } ], "_help": [ { "page": "atoms", "title": "A tibble containing the NIST standard atomic weights", "topics": [ "atoms" ] }, { "page": "calc_km", "title": "Calculate the Kendrick mass", "topics": [ "calc_km" ] }, { "page": "calc_kmd", "title": "Calculate the Kendrick mass defect (KMD)", "topics": [ "calc_kmd" ] }, { "page": "calc_neutral_loss", "title": "Calculate neutral losses from precursor ion mass and fragment ion masses", "topics": [ "calc_neutral_loss" ] }, { "page": "calc_nominal_km", "title": "Calculate the nominal Kendrick mass", "topics": [ "calc_nominal_km" ] }, { "page": "collapse_max", "title": "Collapse intensities of technical replicates by calculating their maximum", "topics": [ "collapse_max" ] }, { "page": "collapse_mean", "title": "Collapse intensities of technical replicates by calculating their mean", "topics": [ "collapse_mean" ] }, { "page": "collapse_median", "title": "Collapse intensities of technical replicates by calculating their median", "topics": [ "collapse_median" ] }, { "page": "collapse_min", "title": "Collapse intensities of technical replicates by calculating their minimum", "topics": [ "collapse_min" ] }, { "page": "convert_from_matrix", "title": "Convert a wide matrix to a tidy tibble", "topics": [ "convert_from_matrix" ] }, { "page": "convert_from_wide", "title": "Convert a wide feature table to a tidy tibble", "topics": [ "convert_from_wide" ] }, { "page": "create_metadata_skeleton", "title": "Create a blank metadata skeleton", "topics": [ "create_metadata_skeleton" ] }, { "page": "filter_blank", "title": "Filter Features based on their occurrence in blank samples", "topics": [ "filter_blank" ] }, { "page": "filter_cv", "title": "Filter Features based on their coefficient of variation", "topics": [ "filter_cv" ] }, { "page": "filter_global_mv", "title": "Filter Features based on the absolute number or fraction of samples it was found in", "topics": [ "filter_global_mv" ] }, { "page": "filter_grouped_mv", "title": "Group-based feature filtering", "topics": [ "filter_grouped_mv" ] }, { "page": "filter_msn", "title": "Filter Features based on occurrence of fragment ions", "topics": [ "filter_msn" ] }, { "page": "filter_mz", "title": "Filter Features based on their mass-to-charge ratios", "topics": [ "filter_mz" ] }, { "page": "filter_neutral_loss", "title": "Filter Features based on occurrence of neutral losses", "topics": [ "filter_neutral_loss" ] }, { "page": "formula_to_mass", "title": "Calculate the monoisotopic mass from a given formula", "topics": [ "formula_to_mass" ] }, { "page": "impute_bpca", "title": "Impute missing values using Bayesian PCA", "topics": [ "impute_bpca" ] }, { "page": "impute_global_lowest", "title": "Impute missing values by replacing them with the lowest observed intensity (global)", "topics": [ "impute_global_lowest" ] }, { "page": "impute_knn", "title": "Impute missing values using nearest neighbor averaging", "topics": [ "impute_knn" ] }, { "page": "impute_lls", "title": "Impute missing values using Local Least Squares (LLS)", "topics": [ "impute_lls" ] }, { "page": "impute_lod", "title": "Impute missing values by replacing them with the Feature 'Limit of Detection'", "topics": [ "impute_lod" ] }, { "page": "impute_mean", "title": "Impute missing values by replacing them with the Feature mean", "topics": [ "impute_mean" ] }, { "page": "impute_median", "title": "Impute missing values by replacing them with the Feature median", "topics": [ "impute_median" ] }, { "page": "impute_min", "title": "Impute missing values by replacing them with the Feature minimum", "topics": [ "impute_min" ] }, { "page": "impute_nipals", "title": "Impute missing values using NIPALS PCA", "topics": [ "impute_nipals" ] }, { "page": "impute_ppca", "title": "Impute missing values using Probabilistic PCA", "topics": [ "impute_ppca" ] }, { "page": "impute_rf", "title": "Impute missing values using random forest", "topics": [ "impute_rf" ] }, { "page": "impute_svd", "title": "Impute missing values using Singular Value Decomposition (SVD)", "topics": [ "impute_svd" ] }, { "page": "impute_user_value", "title": "Impute missing values by replacing them with a user-provided value", "topics": [ "impute_user_value" ] }, { "page": "join_metadata", "title": "Join a featuretable and sample metadata", "topics": [ "join_metadata" ] }, { "page": "msn_calc_nl", "title": "Calculate neutral losses from precursor ion mass and fragment ion masses", "topics": [ "msn_calc_nl" ] }, { "page": "msn_scale", "title": "Scale intensities in MSn spectra to the highest value within each spectrum", "topics": [ "msn_scale" ] }, { "page": "normalize_cyclic_loess", "title": "Normalize intensities across samples using cyclic LOESS normalization", "topics": [ "normalize_cyclic_loess" ] }, { "page": "normalize_factor", "title": "Normalize intensities across samples using a normalization factor", "topics": [ "normalize_factor" ] }, { "page": "normalize_median", "title": "Normalize intensities across samples by dividing by the sample median", "topics": [ "normalize_median" ] }, { "page": "normalize_pqn", "title": "Normalize intensities across samples using a Probabilistic Quotient Normalization (PQN)", "topics": [ "normalize_pqn" ] }, { "page": "normalize_quantile_all", "title": "Normalize intensities across samples using standard Quantile Normalization", "topics": [ "normalize_quantile_all" ] }, { "page": "normalize_quantile_batch", "title": "Normalize intensities across samples using grouped Quantile Normalization with multiple batches", "topics": [ "normalize_quantile_batch" ] }, { "page": "normalize_quantile_group", "title": "Normalize intensities across samples using grouped Quantile Normalization", "topics": [ "normalize_quantile_group" ] }, { "page": "normalize_quantile_smooth", "title": "Normalize intensities across samples using smooth Quantile Normalization (qsmooth)", "topics": [ "normalize_quantile_smooth" ] }, { "page": "normalize_ref", "title": "Normalize intensities across samples using a reference feature", "topics": [ "normalize_ref" ] }, { "page": "normalize_sum", "title": "Normalize intensities across samples by dividing by the sample sum", "topics": [ "normalize_sum" ] }, { "page": "plot_pca", "title": "Draws a scores or loadings plot or performs calculations necessary to draw them manually", "topics": [ "plot_pca" ] }, { "page": "plot_volcano", "title": "Draws a Volcano Plot or performs calculations necessary to draw one manually", "topics": [ "plot_volcano" ] }, { "page": "read_featuretable", "title": "Read a feature table into a tidy tibble", "topics": [ "read_featuretable" ] }, { "page": "read_featuretable_mzmine", "title": "Read a 'full_feature_table' from 'mzmine' into a tidy tibble", "topics": [ "read_featuretable_mzmine" ] }, { "page": "read_mgf", "title": "Read a MGF file into a tidy tibble", "topics": [ "read_mgf" ] }, { "page": "remove_empty_cols", "title": "Remove empty columns from a tibble or data frame", "topics": [ "remove_empty_cols" ] }, { "page": "scale_auto", "title": "Scale intensities of features using autoscale", "topics": [ "scale_auto" ] }, { "page": "scale_center", "title": "Center intensities of features around zero", "topics": [ "scale_center" ] }, { "page": "scale_level", "title": "Scale intensities of features using level scaling", "topics": [ "scale_level" ] }, { "page": "scale_pareto", "title": "Scale intensities of features using Pareto scaling", "topics": [ "scale_pareto" ] }, { "page": "scale_range", "title": "Scale intensities of features using range scaling", "topics": [ "scale_range" ] }, { "page": "scale_vast", "title": "Scale intensities of features using vast scaling", "topics": [ "scale_vast" ] }, { "page": "scale_vast_grouped", "title": "Scale intensities of features using grouped vast scaling", "topics": [ "scale_vast_grouped" ] }, { "page": "summary_featuretable", "title": "General information about a feature table and sample-wise summary", "topics": [ "summary_featuretable" ] }, { "page": "toy_metaboscape", "title": "A small toy data set created from a feature table in MetaboScape style", "topics": [ "toy_metaboscape" ] }, { "page": "toy_metaboscape_metadata", "title": "Sample metadata for the fictional dataset 'toy_metaboscape'", "topics": [ "toy_metaboscape_metadata" ] }, { "page": "toy_mgf", "title": "A small toy data set containing MSn spectra", "topics": [ "toy_mgf" ] }, { "page": "transform_log", "title": "Transforms the intensities by calculating their log", "topics": [ "transform_log" ] }, { "page": "transform_power", "title": "Transforms the intensities by calculating their _n_th root", "topics": [ "transform_power" ] } ], "_pkglogo": "https://github.com/cran/metamorphr/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/cran/metamorphr/raw/HEAD/README.md", "_rundeps": [ "backports", "Biobase", "BiocGenerics", "bit", "bit64", "broom", "cli", "clipr", "codetools", "cpp11", "crayon", "digest", "doRNG", "dplyr", "farver", "foreach", "generics", "ggplot2", "glue", "gtable", "hms", "impute", "isoband", "iterators", "itertools", "labeling", "lattice", "lifecycle", "magrittr", "MASS", "Matrix", "missForest", "pcaMethods", "pillar", "pkgconfig", "prettyunits", "progress", "purrr", "R6", "randomForest", "ranger", "rbibutils", "RColorBrewer", "Rcpp", "RcppEigen", "Rdpack", "readr", "rlang", "rngtools", "S7", "scales", "stringi", "stringr", "tibble", "tidyr", "tidyselect", "tzdb", "utf8", "vctrs", "viridisLite", "vroom", "withr" ], "_vignettes": [ { "source": "conjugate-screening.Rmd", "filename": "conjugate-screening.html", "title": "Conjugate Screening", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Prepare the data set", "Find potential glutathion conjugates", "Some initial filtering", "Characteristic MS/MS fragments", "Characteristic neutral losses", "References" ], "created": "2025-09-01 17:31:50", "modified": "2026-03-04 13:30:02", "commits": 2 }, { "source": "metamorphr.Rmd", "filename": "metamorphr.html", "title": "metamorphr", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "The whole workflow", "Read the required files", "Read the feature table", "Read the sample metadata", "Join them together", "Filter", "Imputate missing values", "Normalize", "Collapse technical replicates", "Plot", "References" ], "created": "2025-09-01 17:31:50", "modified": "2025-09-01 17:31:50", "commits": 1 } ], "_score": 3.6020599913279625, "_indexed": false, "_nocasepkg": "metamorphr", "_universes": [ "cran" ], "_indexurl": "https://yasche.r-universe.dev/metamorphr", "_previous": "0.4.0", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.4.1", "date": "2026-06-10T15:14:58.000Z", "distro": "noble", "commit": "594805f524158e5996dcfc15421ae6b87d89b125", "fileid": "3d4d71f18b2106349f898d1db74bae7c0003d7d13108a9a698d962875c298d09", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/27285854949" }, { "r": "4.6.0", "os": "linux", "version": "0.4.1", "date": "2026-06-10T15:15:26.000Z", "distro": "noble", "commit": "594805f524158e5996dcfc15421ae6b87d89b125", "fileid": "6c762a9c0e507afb683b19a66bccf2973eb8375126adc7d94562027f4baec345", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/27285854949" }, { "r": "4.6.0", "os": "wasm", "version": "0.4.1", "date": "2026-06-10T15:15:32.000Z", "commit": "594805f524158e5996dcfc15421ae6b87d89b125", "fileid": "47c971919abc2d67d285bda533543a68fa6e3d0d3bf19e4c536f8bba3c59633b", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/27285854949" } ] }