Function reference • pmartR

All functions
`DESeq2_wrapper()`	Wrapper for DESeq2 workflow
`RNA_filter()`	RNA Filter Object
`all_subset()`	Identify All Biomolecules for Use in Normalization
`anova_filter()`	Identifies biomolecules to be filtered in preparation for IMD-ANOVA.
`anova_test()`	Tests for a quantiative difference between groups (aka factors, aka main effects)
`applyFilt()`	Apply a S3 filter object to a pmartR S3 object
`as.isobaricpepData()`	Create pmartR Object of Class isobaricpepData
`as.lipidData()`	Create pmartR Object of Class lipidData
`as.metabData()`	Create pmartR Object of Class metabData
`as.multiData()`	Create a `multiData` object from multiple omicsData objects
`as.nmrData()`	Create pmartR Object of Class nmrData
`as.pepData()`	Create pmartR Object of Class pepData
`as.proData()`	Create pmartR Object of Class proData
`as.seqData()`	Create pmartR Object of Class seqData
`as.trelliData()`	Generate an object from omicsData and/or statRes objects to pass to trelliscope building functions
`as.trelliData.edata()`	Generate an object from edata to pass to trelliscope building functions
`bpquant()`	Runs BP-Quant
`bpquant_mod()`	bpquant_mod function
`combine_lipidData()`	Combines two omicsData objects with identical sample information.
`combine_techreps()`	Combine technical replicates of an omicsData object
`complete_mols()`	Identify biomolecules with no missing values across samples
`cor_result()`	Compute Correlation matrix of biomolecule data
`create_comparisonDF()`	Returns data frame with comparisons to be made
`custom_filter()`	Custom Filter Object
`custom_sampnames()`	Creates custom sample names to be used in plots
`cv_filter()`	Pooled Coefficient of Variation (CV) Filter Object
`diffexp_seq()`	Differential Expression for seqData
`dim_reduction()`	Reduce Dimension of Data for Exploratory Data Analysis
`dispersion_est()`	Diagnostic plot for seqData
`.is_edata()`	Test if a file is an edata file
`edata_replace()`	Replace Values Equal to x with y
`edata_summary()`	Creates a list of six Data Frames, one for each summarizing metric
`edata_transform()`	Apply a Transformation to the Data
`edgeR_wrapper()`	Wrapper for edgeR workflow
`fit_surv()`	Basic survival analysis function
`get_check_names()`	DEPRECATED: Fetch the check.names attribute
`get_comparisons()`	Return comparisons of statRes object
`get_data_class()`	Return data_class of statRes or trelliData object
`get_data_info()`	Fetch the data_info attribute
`get_data_norm()`	Fetch the normalization status of the data
`get_data_scale()`	Fetch the current data scale
`get_data_scale_orig()`	Fetch the original data scale
`get_edata_cname()`	Fetch the e_data column name
`get_emeta_cname()`	Fetch the e_meta column name
`get_fdata_cname()`	Fetch the f_data column name
`get_filter_type()`	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.
`get_filters()`	Fetch the filters attribute
`get_group_DF()`	Fetch the group_DF attribute
`get_group_formula()`	Get formula for group design
`get_group_table()`	Get group table
`get_isobaric_info()`	Fetch the isobaric_info attribute
`get_isobaric_norm()`	Fetch the isobaric normalization info
`get_lsmeans()`	Compute the least squares means from a prediction grid and estimated coefficients
`get_meta_info()`	Fetch the meta_info attribute
`get_nmr_info()`	Fetch the nmr_info attribute
`get_nmr_norm()`	Fetch the NMR normalization info
`get_pred_grid()`	Build the prediction grid to compute least squares means.
`get_spans_params()`	Gets the parameters for the highest ranked methods from spans.
`group_comparison_anova()`	Group comparisons for the anova test
`group_comparison_imd()`	Group comparisons for the g-test
`group_designation()`	Creates Attribute of omicsData Object for Group Membership
`gtest_filter()`	Identifies peptides to be filtered out in preparation for IMD-ANOVA.
`imd_anova()`	Test for a qualitative and quantitative difference between groups using IMD and ANOVA, respectively
`imd_test()`	Tests for the independence of missing data across groups (aka factors, aka main effects)
`imdanova_filter()`	IMD-ANOVA Filter Object
`los()`	Identify Biomolecules from the Top L Order Statistics for Use in Normalization
`mad_transform()`	Median Absolute Deviation Transformation
`mean_center()`	Mean Center Transformation
`median_center()`	Median Center Transformation
`missingval_result()`	Creates an object of class naRes (NA Result)
`molecule_filter()`	Molecule Filter Object
`nonmissing_per_group()`	Computes the Number of Non-Missing Data Points by Group
`normRes_tests()`	Test the location and scale parameters from a normalization procedure
`normalize_global()`	Calculate Normalization Parameters and Apply Global Normalization
`normalize_global_basic()`	Normalize e_data within SPANS
`normalize_isobaric()`	Examine and Apply Isobaric Normalization
`normalize_loess()`	Loess Normalization
`normalize_nmr()`	Normalize an Object of Class nmrData
`normalize_quantile()`	Quantile Normalization
`p_adjustment_anova()`	Adjust p-values for multiple comparisons
`plot(<RNAFilt>)`	Plot RNAFilt Object
`plot(<SPANSRes>)`	Plot SPANSRes Object
`plot(<corRes>)`	Plot corRes Object
`plot(<customFilt>)`	Plot customFilt Object
`plot(<cvFilt>)`	Plot cvFilt Object
`plot(<dataRes>)`	Plot dataRes object
`plot(<dimRes>)`	Plot dimRes Object
`plot(<imdanovaFilt>)`	Plot imdanovaFilt Object
`plot(<isobaricnormRes>)`	Plot isobaricnormRes object
`plot(<isobaricpepData>)`	Plot isobaricpepData Object
`plot(<lipidData>)`	Plot lipidData Object
`plot(<metabData>)`	Plot metabData Object
`plot(<moleculeFilt>)`	Plot moleculeFilt Object
`plot(<naRes>)`	Plot naRes Object
`plot(<nmrData>)`	Plot nmrData Object
`plot(<nmrnormRes>)`	Plot nmrnormRes Object
`plot(<normRes>)`	Plot normRes Object
`plot(<pepData>)`	Plot pepData Object
`plot(<proData>)`	Plot proData Object
`plot(<proteomicsFilt>)`	Plot proteomicsFilt Object
`plot(<rmdFilt>)`	Plot rmdFilt Object
`plot(<seqData>)`	Plot seqData Object
`plot(<totalCountFilt>)`	Plot totalCountFilt Object
`plot(<statRes>)`	Plot statRes Object
`plot_km()`	Basic survival analysis plot
`pmartR`	Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data
`pmartR_filter_worker()`	Remove items that need to be filtered out
`ppp()`	Identify Biomolecules from the Proportion Present (PPP) for Use in Normalization
`ppp_rip()`	Identify Proportion of Peptides Present (PPP) and Rank Invariant Peptides (RIP) for Use in Normalization
`pquant()`	Protein Quantitation using Mean or Median Peptide Abundances
`pre_imdanova_melt()`	Create a Melted and Grouped Version of e_data for IMD_ANOVA filter
`prep_flags()`	Extract flag columns from a statRes object
`print(<RNAFilt>)`	print.RNAFilt
`print(<customFilt>)`	print.customFilt
`print(<cvFilt>)`	print.cvFilt
`print(<dataRes>)`	print.dataRes
`print(<imdanovaFilt>)`	print.imdanovaFilt
`print(<lipidData>)`	print.lipidData
`print(<metabData>)`	print.metabData
`print(<moleculeFilt>)`	print.moleculeFilt
`print(<normRes>)`	print.normRes
`print(<pepData>)`	print.pepData
`print(<proData>)`	print.proData
`print(<proteomicsFilt>)`	print.proteomicsFilt
`print(<rmdFilt>)`	print.rmdFilt
`print(<seqData>)`	print.seqData
`print(<totalCountFilt>)`	print.totalCountFilt
`print(<RNAFiltSummary>)`	RNA Filter Print Method
`print(<customFilterSummary>)`	Custom Filter Print Method
`print(<cvFilterSummary>)`	CV Filter Print Method
`print(<imdanovaFilterSummary>)`	IMD-ANOVA Filter Print Method
`print(<moleculeFilterSummary>)`	Molecule Filter Print Method
`print(<proteomicsFilterSummary>)`	Proteomics Filter Print Method
`print(<rmdFilterSummary>)`	RMD Filter Print Method
`print(<totalCountFiltSummary>)`	Total Count Filter Print Method
`protein_quant()`	Protein Quantification
`proteomics_filter()`	Proteomics Filter Object
`qrollup()`	Applies qrollup function
`replace_nas()`	Replace NA with 0
`replace_zeros()`	Replace 0 with NA
`report_dataRes()`	Creates a data frame displaying multiple metrics
`rip()`	Identify Rank-Invariant Biomolcules for Use in Normalization
`rmd_conversion()`	Conversion between log2(RMD) and p-value
`rmd_filter()`	Robust Mahalanobis Distance (RMD) Filter Object
`rrollup()`	Applies rrollup function
`run_group_meancor()`	Calculate the Mean Correlation of a Sample with Respect to Group
`run_kurtosis()`	Calculate the Kurtosis of Sample Runs
`run_mad()`	Calculate the Median Absolute Deviance (MAD) of Sample Runs
`run_prop_missing()`	Calculate the Fraction of Missing Data of Sample Runs
`run_skewness()`	Calculate the Skewness of Sample Runs
`set_check_names()`	DEPRECATED: Set check.names attribute of omicsData object
`spans_make_distribution()`	Creates the list of median p-values used to make the background distribution used to compute the SPANS score in step 2.
`spans_procedure()`	Calculate SPANS Score for a Number of Normalization Methods
`statRes-class`	Summary of statRes Object
`statRes_output()`	Function to take raw output of `imd_anova` and create output for `statRes` object
`summary(<isobaricnormRes>)`	Summary for isobaricnormRes Object
`summary(<nmrnormRes>)`	Summary of nmrnormRes Object
`summary(<pepData>)` `summary(<proData>)` `summary(<lipidData>)` `summary(<metabData>)` `summary(<nmrData>)` `summary(<seqData>)`	Produce a basic summary of a pmartR omicsData S3 Object
`summary(<normRes>)` `summary(<SPANSRes>)` `summary(<dimRes>)` `summary(<corRes>)`	Summary of pmartR Analysis Functions
`summary(<trelliData>)`	Summarizes potential plotting options for a trelliData object
`summary(<RNAFilt>)`	RNA Filter Summary
`summary(<customFilt>)`	Custom Filter Summary
`summary(<cvFilt>)`	Coefficient of Variation (CV) Filter Summary
`summary(<imdanovaFilt>)`	IMD-ANOVA Filter Summary
`summary(<moleculeFilt>)`	Molecule Filter Summary
`summary(<proteomicsFilt>)`	Proteomics Filter Summary
`summary(<rmdFilt>)`	RMD Filter Summary
`summary(<totalCountFilt>)`	Total Count Filter Summary
`summary_km()`	Basic survival analysis summary
`surv_designation()`	Create a "surv_DF" attribute so that survival analysis can be implemented.
`take_diff()`	Compute pairwise differences
`total_count_filter()`	Total Count Filter Object
`trelli_abundance_boxplot()`	Boxplot trelliscope building function for abundance data
`trelli_abundance_heatmap()`	Heatmap trelliscope building function for abundance data
`trelli_abundance_histogram()`	Histogram trelliscope building function for abundance data
`trelli_foldchange_bar()`	Bar chart trelliscope building function for fold_change
`trelli_foldchange_boxplot()`	Boxplot trelliscope building function for fold_changes
`trelli_foldchange_heatmap()`	Heatmap trelliscope building function for fold_change
`trelli_foldchange_volcano()`	Volcano trelliscope building function for fold_change
`trelli_missingness_bar()`	Bar chart trelliscope building function for missing data
`trelli_panel_by()`	Set the "panel_by" variable for a trelliData object
`trelli_precheck()`	Performs initial checks for trelliData objects
`trelli_pvalue_filter()`	Filter a paneled trelliData object by a p-value
`trelli_rnaseq_boxplot()`	Boxplot trelliscope building function for RNA-seq data
`trelli_rnaseq_heatmap()`	Heatmap trelliscope building function for RNA-seq data
`trelli_rnaseq_histogram()`	Histogram trelliscope building function for RNA-Seq data
`trelli_rnaseq_nonzero_bar()`	Bar chart trelliscope building function for Non-Zero counts in RNA-seq data
`vector_replace()`	Replace x with y for a single vector
`voom_wrapper()`	Wrapper for limma-voom workflow
`zrollup()`	Applies zrollup function
`zscore_transform()`	Z-Score Transformation

Reference

All functions