Taxa {DECIPHER} | R Documentation

## Taxa training and testing objects

### Description

Taxonomic classification is the process of assigning an organism a label that is part of a taxonomic hierarchy (e.g., Phylum, Class, Order, Family, Genus). Here, labels are assigned based on an organism's DNA or RNA sequence at a rank level determined by the classification's confidence. Class `Taxa` provides objects and functions for storing and viewing training and testing objects used in taxonomic classification.

### Usage

    ## S3 method for class 'Taxa'
    plot(x,
        y = NULL,
        showRanks = TRUE,
        n = NULL,
        ...)

    ## S3 method for class 'Taxa'
    print(x,
         ...)

    ## S3 method for class 'Taxa'
    x[i, j, threshold]

### Arguments

`x` | An object of class `Taxa` with subclass `Train` or `Test`.
`y` | An (optional) object of class `Taxa` with the opposite subclass as `x`.
`showRanks` | Logical specifying whether to show all rank levels when plotting an object of class `Taxa` and subclass `Test`. If `TRUE` (the default), then ranks are shown as (colored) concentric rings with radial lines delimiting taxa boundaries.
`n` | Numeric vector giving the frequency of each classification if `x` or `y` is an object of subclass `Test`, or the default (`NULL`) to treat all classifications as occurring once. Typically, specifying `n` is useful when the classifications represent varying numbers of observations, e.g., when only unique sequences were originally classified.
`...` | Other optional parameters.
`i` | Numeric or character vector of indices to extract from objects of class `Taxa` with subclass `Test`.
`j` | Numeric or character vector of rank levels to extract from objects of class `Taxa` with subclass `Test`.
`threshold` | Numeric specifying the confidence `threshold` at which to truncate the output taxonomic classifications. Note that `threshold` must be higher than the original for the classifications to change.

### Details

Objects of class `Taxa` are stored as lists, and can have either subclass `Train` or `Test`. The function `LearnTaxa` returns an object of subclass `Train`, while the function `IdTaxa` can return an object of class `Test`.

`Train`ing objects are built from a set of reference sequences with known taxonomic classifications. List elements contain information required by `IdTaxa` for assigning a classification to test sequences.

`Test`ing objects can be generated by `IdTaxa` from a `Train`ing object and a set of test sequences. Each list element contains the taxon, confidence, and (optionally) rank name of the taxonomic assignment.

The information stored in `Taxa` can be visualized with the `plot` function or displayed with `print`. Only objects of subclass `Train` can be subsetted without losing their class.

### Author(s)

Erik Wright eswright@pitt.edu

### See Also

`LearnTaxa`, `IdTaxa`

### Examples

    data("TrainingSet_16S")
    plot(TrainingSet_16S)

    # import test sequences
    fas <- system.file("extdata", "Bacteria_175seqs.fas", package="DECIPHER")
    dna <- readDNAStringSet(fas)

    # remove any gaps in the sequences
    dna <- RemoveGaps(dna)

    # classify the test sequences
    ids <- IdTaxa(dna, TrainingSet_16S, strand="top")
    ids

    plot(ids) # plot all rank levels
    plot(ids[, 1:4]) # plot the first rank levels
    plot(ids[j=c("rootrank", "class", "genus")]) # plot specific rank levels
    plot(ids[threshold=70]) # plot high confidence classifications

[Package DECIPHER version 2.22.0 Index]