{ "_id": "6a1eee48b401979e7341292d", "Package": "pmartR", "Type": "Package", "Title": "Panomics Marketplace - Quality Control and Statistical Analysis\nfor Panomics Data", "Version": "2.5.1", "Date": "2025-10-21", "Authors@R": "c(\nperson(\"Lisa\", \"Bramer\", email = \"lisa.bramer@pnnl.gov\", role = c(\"aut\", \"cre\")),\nperson(\"Kelly\", \"Stratton\", email = \"kelly.stratton@pnnl.gov\", role = c(\"aut\")),\nperson(\"Daniel\", \"Claborne\", email = \"daniel.claborne@pnnl.gov\", role = c(\"aut\")),\nperson(\"Evan\", \"Glasscock\", role = c(\"ctb\")),\nperson(\"Rachel\", \"Richardson\", role = c(\"ctb\")),\nperson(\"David\", \"Degnan\", role=c(\"ctb\")),\nperson(\"Evan\", \"Martin\", role=c(\"ctb\"))\n)", "Description": "Provides functionality for quality control processing and\nstatistical analysis of mass spectrometry (MS) omics data, in\nparticular proteomic (either at the peptide or the protein\nlevel), lipidomic, and metabolomic data, as well as RNA-seq\nbased count data and nuclear magnetic resonance (NMR) data.\nThis includes data transformation, specification of groups that\nare to be compared against each other, filtering of features\nand/or samples, data normalization, data summarization\n(correlation, PCA), and statistical comparisons between defined\ngroups. Implements methods described in: Webb-Robertson et al.\n(2014) . Webb-Robertson et al.\n(2011) . Matzke et al. (2011)\n. Matzke et al. (2013)\n. Polpitiya et al. (2008)\n. Webb-Robertson et al.\n(2010) .", "License": "BSD_2_clause + file LICENSE", "URL": "https://pmartr.github.io/pmartR/, https://github.com/pmartR/pmartR", "BugReports": "https://github.com/pmartR/pmartR/issues", "biocViews": "", "Additional_repositories": "https://pmartR.github.io/drat", "RoxygenNote": "7.3.2", "Encoding": "UTF-8", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://pmartr.r-universe.dev", "Date/Publication": "2025-10-21 19:33:44 UTC", "RemoteUrl": "https://github.com/pmartr/pmartr", "RemoteRef": "HEAD", "RemoteSha": "e46f2f0297939ad8cbe74a4f0df88ae535b8de0b", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-19 08:50:33 UTC", "User": "root" }, "Author": "Lisa Bramer [aut, cre],\nKelly Stratton [aut],\nDaniel Claborne [aut],\nEvan Glasscock [ctb],\nRachel Richardson [ctb],\nDavid Degnan [ctb],\nEvan Martin [ctb]", "Maintainer": "Lisa Bramer ", "MD5sum": "2de3bede93f732e6bd4fc11cee4c7887", "_user": "pmartr", "_type": "src", "_file": "pmartR_2.5.1.tar.gz", 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"title": "Custom Filter Object", "topics": [ "custom_filter" ] }, { "page": "custom_sampnames", "title": "Creates custom sample names to be used in plots", "topics": [ "custom_sampnames" ] }, { "page": "cv_filter", "title": "Pooled Coefficient of Variation (CV) Filter Object", "topics": [ "cv_filter" ] }, { "page": "DESeq2_wrapper", "title": "Wrapper for DESeq2 workflow", "topics": [ "DESeq2_wrapper" ] }, { "page": "diffexp_seq", "title": "Differential Expression for seqData", "topics": [ "diffexp_seq" ] }, { "page": "dim_reduction", "title": "Reduce Dimension of Data for Exploratory Data Analysis", "topics": [ "dim_reduction" ] }, { "page": "dispersion_est", "title": "Diagnostic plot for seqData", "topics": [ "dispersion_est" ] }, { "page": "edata_replace", "title": "Replace Values Equal to x with y", "topics": [ "edata_replace" ] }, { "page": "edata_summary", "title": "Creates a list of six Data Frames, one for each summarizing metric", "topics": [ "edata_summary" ] }, { "page": "edata_transform", "title": "Apply a Transformation to the Data", "topics": [ "edata_transform" ] }, { "page": "edgeR_wrapper", "title": "Wrapper for edgeR workflow", "topics": [ "edgeR_wrapper" ] }, { "page": "fit_surv", "title": "Basic survival analysis function", "topics": [ "fit_surv" ] }, { "page": "get_check_names", "title": "*DEPRECATED*: Fetch the check.names attribute", "topics": [ "get_check_names" ] }, { "page": "get_comparisons", "title": "Return comparisons of statRes object", "topics": [ "get_comparisons" ] }, { "page": "get_data_class", "title": "Return data_class of statRes or trelliData object", "topics": [ "get_data_class" ] }, { "page": "get_data_info", "title": "Fetch the data_info attribute", "topics": [ "get_data_info" ] }, { "page": "get_data_norm", "title": "Fetch the normalization status of the data", "topics": [ "get_data_norm" ] }, { "page": "get_data_scale", "title": "Fetch the current data scale", "topics": [ "get_data_scale" ] }, { "page": "get_data_scale_orig", "title": "Fetch the original data scale", "topics": [ "get_data_scale_orig" ] }, { "page": "get_edata_cname", "title": "Fetch the e_data column name", "topics": [ "get_edata_cname" ] }, { "page": "get_emeta_cname", "title": "Fetch the e_meta column name", "topics": [ "get_emeta_cname" ] }, { "page": "get_fdata_cname", "title": "Fetch the f_data column name", "topics": [ "get_fdata_cname" ] }, { "page": "get_filter_type", "title": "Extracts the types of filters that have been applied. This function will be used at the beginning of the applyFilt function to give a warning if the same type of filter has already been applied.", "topics": [ "get_filter_type" ] }, { "page": "get_filters", "title": "Fetch the filters attribute", "topics": [ "get_filters" ] }, { "page": "get_group_DF", "title": "Fetch the group_DF attribute", "topics": [ "get_group_DF" ] }, { "page": "get_group_formula", "title": "Get formula for group design", "topics": [ "get_group_formula" ] }, { "page": "get_group_table", "title": "Get group table", "topics": [ "get_group_table" ] }, { "page": "get_isobaric_info", "title": "Fetch the isobaric_info attribute", "topics": [ "get_isobaric_info" ] }, { "page": "get_isobaric_norm", "title": "Fetch the isobaric normalization info", "topics": [ "get_isobaric_norm" ] }, { "page": "get_lsmeans", "title": "Compute the least squares means from a prediction grid and estimated coefficients", "topics": [ "get_lsmeans" ] }, { "page": "get_meta_info", "title": "Fetch the meta_info attribute", "topics": [ "get_meta_info" ] }, { "page": "get_nmr_info", "title": "Fetch the nmr_info attribute", "topics": [ "get_nmr_info" ] }, { "page": "get_nmr_norm", "title": "Fetch the NMR normalization info", "topics": [ "get_nmr_norm" ] }, { "page": "get_pred_grid", "title": "Build the prediction grid to compute least squares means.", "topics": [ "get_pred_grid" ] }, { "page": "get_spans_params", "title": "Gets the parameters for the highest ranked methods from spans.", "topics": [ "get_spans_params" ] }, { "page": "group_comparison_anova", "title": "Group comparisons for the anova test", "topics": [ "group_comparison_anova" ] }, { "page": "group_comparison_imd", "title": "Group comparisons for the g-test", "topics": [ "group_comparison_imd" ] }, { "page": "group_designation", "title": "Creates Attribute of omicsData Object for Group Membership", "topics": [ "group_designation" ] }, { "page": "gtest_filter", "title": "Identifies biomolecules to be filtered out in preparation for IMD-ANOVA.", "topics": [ "gtest_filter" ] }, { "page": "imd_anova", "title": "Test for a qualitative and quantitative difference between groups using IMD and ANOVA, respectively", "topics": [ "imd_anova" ] }, { "page": "imd_test", "title": "Tests for the independence of missing data across groups (aka factors, aka main effects)", "topics": [ "imd_test" ] }, { "page": "imdanova_filter", "title": "IMD-ANOVA Filter Object", "topics": [ "imdanova_filter" ] }, { "page": "los", "title": "Identify Biomolecules from the Top L Order Statistics for Use in Normalization", "topics": [ "los" ] }, { "page": "mad_transform", "title": "Median Absolute Deviation Transformation", "topics": [ "mad_transform" ] }, { "page": "mean_center", "title": "Mean Center Transformation", "topics": [ "mean_center" ] }, { "page": "median_center", "title": "Median Center Transformation", "topics": [ "median_center" ] }, { "page": "missingval_result", "title": "Creates an object of class naRes (NA Result)", "topics": [ "missingval_result" ] }, { "page": "molecule_filter", "title": "Molecule Filter Object", "topics": [ "molecule_filter" ] }, { "page": "nonmissing_per_group", "title": "Computes the Number of Non-Missing Data Points by Group", "topics": [ "nonmissing_per_group" ] }, { "page": "normalize_global", "title": "Calculate Normalization Parameters and Apply Global Normalization", "topics": [ "normalize_global" ] }, { "page": "normalize_global_basic", "title": "Normalize e_data within SPANS", "topics": [ "normalize_global_basic" ] }, { "page": "normalize_isobaric", "title": "Examine and Apply Isobaric Normalization", "topics": [ "normalize_isobaric" ] }, { "page": "normalize_loess", "title": "Loess Normalization", "topics": [ "normalize_loess" ] }, { "page": "normalize_nmr", "title": "Normalize an Object of Class nmrData", "topics": [ "normalize_nmr" ] }, { "page": "normalize_quantile", "title": "Quantile Normalization", "topics": [ "normalize_quantile" ] }, { "page": "normalize_zero_one_scaling", "title": "Scale from zero to one", "topics": [ "normalize_zero_one_scaling" ] }, { "page": "normRes_tests", "title": "Test the location and scale parameters from a normalization procedure", "topics": [ "normRes_tests" ] }, { "page": "p_adjustment_anova", "title": "Adjust p-values for multiple comparisons", "topics": [ "p_adjustment_anova" ] }, { "page": "plot_km", "title": "Basic survival analysis plot", "topics": [ "plot_km" ] }, { "page": "plot-corRes", "title": "Plot corRes Object", "topics": [ "plot.corRes" ] }, { "page": "plot-customFilt", "title": "Plot customFilt Object", "topics": [ "plot.customFilt" ] }, { "page": "plot-cvFilt", "title": "Plot cvFilt Object", "topics": [ "plot.cvFilt" ] }, { "page": "plot-dataRes", "title": "Plot dataRes object", "topics": [ "plot.dataRes" ] }, { "page": "plot-dimRes", "title": "Plot dimRes Object", "topics": [ "plot.dimRes" ] }, { "page": "plot-imdanovaFilt", "title": "Plot imdanovaFilt Object", "topics": [ "plot.imdanovaFilt" ] }, { "page": "plot-isobaricnormRes", "title": "Plot isobaricnormRes object", "topics": [ "plot.isobaricnormRes" ] }, { "page": "plot-isobaricpepData", "title": "Plot isobaricpepData Object", "topics": [ "plot.isobaricpepData" ] }, { "page": "plot-lipidData", "title": "Plot lipidData Object", "topics": [ "plot.lipidData" ] }, { "page": "plot-metabData", "title": "Plot metabData Object", "topics": [ "plot.metabData" ] }, { "page": "plot-moleculeFilt", "title": "Plot moleculeFilt Object", "topics": [ "plot.moleculeFilt" ] }, { "page": "plot-naRes", "title": "Plot naRes Object", "topics": [ "plot.naRes" ] }, { "page": "plot-nmrData", "title": "Plot nmrData Object", "topics": [ "plot.nmrData" ] }, { "page": "plot-nmrnormRes", "title": "Plot nmrnormRes Object", "topics": [ "plot.nmrnormRes" ] }, { "page": "plot-normRes", "title": "Plot normRes Object", "topics": [ "plot.normRes" ] }, { "page": "plot-pepData", "title": "Plot pepData Object", "topics": [ "plot.pepData" ] }, { "page": "plot-proData", "title": "Plot proData Object", "topics": [ "plot.proData" ] }, { "page": "plot-proteomicsFilt", "title": "Plot proteomicsFilt Object", "topics": [ "plot.proteomicsFilt" ] }, { "page": "plot-rmdFilt", "title": "Plot rmdFilt Object", "topics": [ "plot.rmdFilt" ] }, { "page": "plot-RNAFilt", "title": "Plot RNAFilt Object", "topics": [ "plot.RNAFilt" ] }, { "page": "plot-seqData", "title": "Plot seqData Object", "topics": [ "plot.seqData" ] }, { "page": "plot-SPANSRes", "title": "Plot SPANSRes Object", "topics": [ "plot.SPANSRes" ] }, { "page": "plot.statRes", "title": "Plot statRes Object", "topics": [ "plot.statRes" ] }, { "page": "plot-totalCountFilt", "title": "Plot totalCountFilt Object", "topics": [ "plot.totalCountFilt" ] }, { "page": "pmartR", "title": "Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data", "topics": [ "pmartR-package", "pmartR" ] }, { "page": "pmartR_filter_worker", "title": "Remove items that need to be filtered out", "topics": [ "pmartR_filter_worker" ] }, { "page": "ppp", "title": "Identify Biomolecules from the Proportion Present (PPP) for Use in Normalization", "topics": [ "ppp" ] }, { "page": "ppp_rip", "title": "Identify Proportion of Peptides Present (PPP) and Rank Invariant Peptides (RIP) for Use in Normalization", "topics": [ "ppp_rip" ] }, { "page": "pquant", "title": "Protein Quantitation using Mean or Median Peptide Abundances", "topics": [ "pquant" ] }, { "page": "pre_imdanova_melt", "title": "Create a Melted and Grouped Version of e_data for IMD_ANOVA filter", "topics": [ "pre_imdanova_melt" ] }, { "page": "prep_flags", "title": "Extract flag columns from a statRes object", "topics": [ "prep_flags" ] }, { "page": "print-customFilt", "title": "print.customFilt", "topics": [ "print.customFilt" ] }, { "page": "print.customFilterSummary", "title": "Custom Filter Print Method", "topics": [ "print.customFilterSummary" ] }, { "page": "print-cvFilt", "title": "print.cvFilt", "topics": [ "print.cvFilt" ] }, { "page": "print.cvFilterSummary", "title": "CV Filter Print Method", "topics": [ "print.cvFilterSummary" ] }, { "page": "print-dataRes", "title": "print.dataRes", "topics": [ "print.dataRes" ] }, { "page": "print-imdanovaFilt", "title": "print.imdanovaFilt", "topics": [ "print.imdanovaFilt" ] }, { "page": "print.imdanovaFilterSummary", "title": "IMD-ANOVA Filter Print Method", "topics": [ "print.imdanovaFilterSummary" ] }, { "page": "print-lipidData", "title": "print.lipidData", "topics": [ "print.lipidData" ] }, { "page": "print-metabData", "title": "print.metabData", "topics": [ "print.metabData" ] }, { "page": "print-moleculeFilt", "title": "print.moleculeFilt", "topics": [ "print.moleculeFilt" ] }, { "page": "print.moleculeFilterSummary", "title": "Molecule Filter Print Method", "topics": [ "print.moleculeFilterSummary" ] }, { "page": "print-normRes", "title": "print.normRes", "topics": [ "print.normRes" ] }, { "page": "print-pepData", "title": 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(RMD) Filter Object", "topics": [ "rmd_filter" ] }, { "page": "RNA_filter", "title": "RNA Filter Object", "topics": [ "RNA_filter" ] }, { "page": "rrollup", "title": "Applies rrollup function", "topics": [ "rrollup" ] }, { "page": "run_group_meancor", "title": "Calculate the Mean Correlation of a Sample with Respect to Group", "topics": [ "run_group_meancor" ] }, { "page": "run_kurtosis", "title": "Calculate the Kurtosis of Sample Runs", "topics": [ "run_kurtosis" ] }, { "page": "run_mad", "title": "Calculate the Median Absolute Deviance (MAD) of Sample Runs", "topics": [ "run_mad" ] }, { "page": "run_prop_missing", "title": "Calculate the Fraction of Missing Data of Sample Runs", "topics": [ "run_prop_missing" ] }, { "page": "run_skewness", "title": "Calculate the Skewness of Sample Runs", "topics": [ "run_skewness" ] }, { "page": "set_check_names", "title": "*DEPRECATED*: Set check.names attribute of omicsData object", "topics": [ "set_check_names" ] }, { "page": 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