filter_peaks_by_blank {pmp} | R Documentation

## Filter features by blank samples

### Description

Metabolomics datasets often contain many features of non-biological origin e.g. those associated with extraction and analysis solvents. This tool facilitates the removal of such features from the data matrix, as defined using an appropriate blank sample.

### Usage

    filter_peaks_by_blank(
      df,
      fold_change,
      classes,
      blank_label,
      qc_label = NULL,
      remove_samples = TRUE,
      remove_peaks = TRUE,
      fraction_in_blank = 0
    )

### Arguments

`df` | A matrix-like (e.g. an ordinary matrix, a data frame) or RangedSummarizedExperiment-class object with all values of class `numeric()` or `integer()` of peak intensities, areas or other quantitative characteristic.
`fold_change` | `numeric(1)`, fold_change minimum fold change between analytical and blank samples.
`classes` | `character()`, vector of class labels. Must be the same length as the number of sample in the input peak table. If input is `SummarizedExperiment` object, use `SummarizedExperiment_object$meta_data_column_name`.
`blank_label` | `character(1)`, class label used to identify blank samples.
`qc_label` | `character(1)` or `NULL`, class label used to identify QC samples.
`remove_samples` | `logical(1)`, remove blank samples from peak matrix or not.
`remove_peaks` | `logical(1)`, remove filtered features from peak matrix or not.
`fraction_in_blank` | `numeric(1)`, value between 0 to 1 to specify fraction in how many blanks peaks should be present.

### Details

If parameter `qc_label` is not `NULL`, QC samples which will be used to calculate the median signal intensity.

### Value

Object of class `SummarizedExperiment`. If input data are a matrix-like (e.g. an ordinary matrix, a data frame) object, function returns `numeric()` matrix-like object of filtered data set. Function `flags` are added to the object `attributes` and is a DataFrame-class with five columns. The same `DataFrame` object containing flags is added to `rowData()` element of `SummarizedExperiment` object as well.
Columns in `rowData()` or `flags` element contain:
`median_non_blanks` median intensities of features of non-blank samples;
`median_blanks` median intensities of features of blank samples;
`fold_change` fold change between analytical and blank samples;
`blank_flags` `integer()`, if 0 feature is flagged to be removed;
`blank_fraction_flags` `numeric()`, fraction in how many blank samples peaks is present.

### Examples

    df <- MTBLS79[ ,MTBLS79$Batch == 1]
    df$Class[1:2] <- "Blank"
    out <- filter_peaks_by_blank(df=df, fold_change=1.2,
       classes=df$Class, blank_label="Blank", qc_label=NULL,
       remove_samples=FALSE, remove_peaks=TRUE, fraction_in_blank=0)

[Package pmp version 1.0.0 Index]