formatForAnalysis: Format data for analysis
In ASICS: Automatic Statistical Identification in Complex Spectra

Description Usage Arguments Value Examples

View source: R/analysis_on_quantification.R

Create an object of class SummarizedExperiment to use in functions pca, oplsda or kruskalWallis.

formatForAnalysis(
  data,
  design = NULL,
  feature_info = NULL,
  zero.threshold = 100,
  zero.group = NULL,
  outliers = NULL
)

`data`	A data frame containing omics dataset with samples in columns and features of interest in rows (metabolites/buckets...).
`design`	A data frame describing the colums of `data` with at least two columns, the first one corresponding to the column names of `data`. Default to NULL (in which case, the column names of `data` are used for study design).
`feature_info`	A data frame describing the rows of `data` with at least two columns, the first one corresponding to the row names of `data`. Default to NULL (in which case, the row names of `data` are used for feature information).
`zero.threshold`	Remove features having a proportion of zeros larger than or equal to `zero.threshold`. Default to `100`.
`zero.group`	Variable name of design data frame specifying the group variable used to remove features with a proportion of zeros larger than or equal to `zero.threshold` within the group. Default to `NULL`, no group.
`outliers`	Names of the outliers (samples) to remove.

An object of type SummarizedExperiment with metabolite data given as buckets or quantified metabolites.

# Import quantification results
if (require("ASICSdata", quietly = TRUE)) {
  quantif_path <- system.file("extdata", "results_ASICS.txt",
                              package = "ASICSdata")
  quantification <- read.table(quantif_path, header = TRUE, row.names = 1)

  # Import design
  design <- read.table(system.file("extdata", "design_diabete_example.txt",
                                   package = "ASICSdata"), header = TRUE)

  # Create object for analysis and remove features with more than 25% of
  # zeros
  analysis_obj <- formatForAnalysis(quantification,
                                    design = design,
                                    zero.threshold = 25,
                                    zero.group = "condition")
}