filter_peaks_by_fraction {pmp} | R Documentation

## Filter features by fraction of missing values

### Description

Metabolomics datasets often contain 'features' with irreproducible peak intensity values, or with large numbers of missing values. This tool facilitates the remove of such features from a data matrix, based upon the relative proportion (minimum fraction) of samples containing non-missing values.

### Usage

    filter_peaks_by_fraction(
      df,
      min_frac,
      classes = NULL,
      method = "QC",
      qc_label = "QC",
      remove_peaks = TRUE
    )

### 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.
`min_frac` | `numeric(1)`, value between 0 and 1, a threshold of fraction of detection.
`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`.
`method` | `character(1)`, method to use. `QC` - within QC samples, `within` - within each sample class or `across` - across all samples.
`qc_label` | `character(1)` or `NULL`, class label used to identify QC samples.
`remove_peaks` | `logical(1)`, remove filtered features from peak matrix or not.

### 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 `fractions` of missing values per feature within QC samples (mehtod `QC`), across (method `across`) or within (mehtod `within`) each sample group.

### Examples

    df <- MTBLS79[ ,MTBLS79$Batch == 1]
    out <- filter_peaks_by_fraction(df=df, min_frac=1,
        classes=df$Class, method='QC', qc_label='QC')

    out <- filter_peaks_by_fraction(df=df, min_frac=1,
        classes=df$Class, method='across', qc_label='QC')

    out <- filter_peaks_by_fraction(df=df, min_frac=1,
        classes=df$Class, method='within', qc_label='QC')

[Package pmp version 1.0.0 Index]