artmsAnalysisQuantifications {artMS} | R Documentation

## Analysis of the Relative Quantifications

### Description

Analysis of relative quantifications, including:

- Annotations

- Summary files in different format (xls, txt) and shapes (long, wide)

- Numerous summary plots

- Enrichment analysis using Gprofiler

- PCA of quantifications

- Clustering analysis

- Basic imputation of missing values

### Usage

    artmsAnalysisQuantifications(
      log2fc_file,
      modelqc_file,
      species,
      output_dir = "analysis_quant",
      outliers = c("keep", "iqr", "std"),
      enrich = TRUE,
      l2fc_thres = 1,
      choosePvalue = c("adjpvalue", "pvalue"),
      isBackground = "nobackground",
      isPtm = "global",
      mnbr = 2,
      isFluomics = FALSE,
      pathogen = "nopathogen",
      plotPvaluesLog2fcDist = TRUE,
      plotAbundanceStats = TRUE,
      plotReproAbundance = TRUE,
      plotCorrConditions = TRUE,
      plotCorrQuant = TRUE,
      plotPCAabundance = TRUE,
      plotFinalDistributions = TRUE,
      plotPropImputation = TRUE,
      plotHeatmapsChanges = TRUE,
      plotTotalQuant = TRUE,
      plotClusteringAnalysis = TRUE,
      data_object = FALSE,
      verbose = TRUE
    )

### Arguments

`log2fc_file` | (char) MSstats results file location
`modelqc_file` | (char) MSstats modelqc file location
`species` | (char) Select one species. Species currently supported for a full analysis (including enrichment analysis): HUMAN MOUSE To find out species supported only for annotation check `?artmsIsSpeciesSupported()`
`output_dir` | (char) Name for the folder to output the results from the function. Default is current directory (recommended to provide a new folder name).
`outliers` | (char) It allows to keep or remove outliers. Options: `keep` (default): it keeps outliers 'keep', 'iqr', 'std' `iqr` (recommended): remove outliers +/- 6 x Interquartile Range (IQR) `std` : 6 x standard deviation
`enrich` | (logical) Performed enrichment analysis using GprofileR? Only available for species HUMAN and MOUSE. `TRUE` (default if "human" or "mouse" are the species) or `FALSE`
`l2fc_thres` | (int) log2fc cutoff for enrichment analysis (default, `l2fc_thres = 1.5`)
`choosePvalue` | (char) specify whether `pvalue` or `adjpvalue` should use for the analysis. The default option is `adjpvalue` (multiple testing correction). But if the number of biological replicates for a given experiment is too low (for example n = 2), then `choosePvalue = pvalue` is recommended.
`isBackground` | (char) background of gene names for enrichment analysis. `nobackground` (default) will use the total number of genes detected. Alternatively provided the file path name to the background gene list.
`isPtm` | (char) Is a ptm-site quantification? `global` (default), `ptmsites` (for site specific analysis), `ptmph` (Jeff Johnson script output evidence file)
`mnbr` | (int) minimal number of biological replicates for imputation and filtering. Default: `mnbr = 2` (Proteins must be found in one of the conditions in at least 2 of the biological replicates)
`isFluomics` | (logical) Does this data belong to the FluOMICs project? `TRUE` or `FALSE` (default)
`pathogen` | (char) Is there a pathogen in the dataset as well? if it does not, then use `pathogen = nopathogen` (default). Pathogens available: `tb` (Tuberculosis), `lpn` (Legionella)
`plotPvaluesLog2fcDist` | (logical) If `TRUE` (default) plots pvalues and log2fc distributions
`plotAbundanceStats` | (logical) If `TRUE` (default) plots stats graphs about abundance values
`plotReproAbundance` | (logical) If `TRUE` plots reproducibility based on normalized abundance values
`plotCorrConditions` | (logical) If `TRUE` plots correlation between the different conditions
`plotCorrQuant` | (logical) if `TRUE` plots correlation between the available quantifications (comparisons)
`plotPCAabundance` | (logical) if `TRUE` performs PCA analysis of conditions using normalized abundance values
`plotFinalDistributions` | (logical) if `TRUE` plots distribution of both log2fc and pvalues
`plotPropImputation` | (logical) if `TRUE` plots proportion of overall imputation
`plotHeatmapsChanges` | (logical) if `TRUE` plots heatmaps of quantified changes (both all and significant only)
`plotTotalQuant` | (logical) if `TRUE` plots barplot of total number of quantifications per comparison
`plotClusteringAnalysis` | (logical) if `TRUE` performs clustering analysis between quantified comparisons (more than 1 comparison required)
`data_object` | (logical) flag to indicate whether the required files are data objects. Default is FALSE
`verbose` | (logical) `TRUE` (default) shows function messages

### Value

(data.frame) summary of quantifications, including annotations, enrichments, etc

### Examples

    # Testing that the files cannot be empty
    artmsAnalysisQuantifications(log2fc_file = NULL,
                                  modelqc_file = NULL,
                                  species = NULL,
                                  output_dir = NULL)

[Package artMS version 1.6.5 Index]