summarize.features {SIAMCAT} | R Documentation

## Summarize features

### Description

This function summarize features on a specific taxonomic level

### Usage

    summarize.features(siamcat, level = 'g__',
                        feature.type='original', verbose=1)

### Arguments

`siamcat` | object of class siamcat-class
`level` | string, at which level to summarize (e.g. `g__` = genus)
`feature.type` | string, on which type of features should the function work? Can be either `"original"`, `"filtered"`, or `"normalized"`. Please only change this paramter if you know what you are doing!
`verbose` | integer, control output: `0` for no output at all, `1` for only information about progress and success, `2` for normal level of information and `3` for full debug information, defaults to `1`

### Details

This function will summarize features at different taxonomic levels, e.g. transform species-level relative abundance into genus-level taxonomic profiles.

The function expects feature names which encode taxonomic information, e.g.

`k__Bacteria;p__Actinobacteria;c__Actinobacteria;o__Acidimicrobiales;..`

Then, for a given taxonomic level (e.g. `g__`), the function will sum up all the relative abundances of features belonging to the same group at that specific taxonomic level.

Please note that this function is currently maturing and not necessarily reliable!!!

### Value

object of class siamcat-class with a summarized feature table

### Examples

    ## load the phyloseq example data
    data("GlobalPatterns")
    feat <- otu_table(GlobalPatterns)[1:500,]
    label <- create.label(meta=sample_data(GlobalPatterns),
        label = "SampleType",
        case = c("Freshwater", "Freshwater (creek)", "Ocean"))
    # rename features to create feature names containing taxonomic information
    temp <- tax_table(GlobalPatterns)[1:500,]
    test <- apply(temp, 1, FUN=function(vec){
        out <- ''
        for (i in seq_along(vec)){
            end <- ifelse(i == ncol(temp), '', ';')
            x <- colnames(temp)[i]
            x2 <- tolower(substr(x, 1, 1))
            out <- paste0(out, x2, '__', vec[i], end)
        }
        return(out)})
    rownames(feat) <- test
    # run the constructor function
    siamcat <- siamcat(feat=feat, label=label, verbose=1)
    siamcat <- summarize.features(siamcat, level='g__', verbose=3)

[Package SIAMCAT version 1.6.0 Index]