aldex.clr-class: The aldex.clr class

In ALDEx2: Analysis Of Differential Abundance Taking Sample Variation Into Account

Description

The aldex.clr S4 class is a class which stores the data generated by the aldex.clr method.

Details

An aldex.clr object contains the Monte Carlo Dirochlet instances derived from estimating the technical variance of the raw read count data. It is created by the aldex.clr.function, which is invoked by the aldex.clr method. It consists of four attributes: the sample names, the feature names, the conditions vector (assigns each sample to a condition), and the Monte Carlo Dirochlet instances themselves. These can be accessed, along with information about the length of some attributes. A single Monte Carlo instance can also be retrieved.

Value

The aldex.clr object contains the clr transformed values for each Monte-Carlo Dirichlet instance, which can be accessed through getMonteCarloInstances(x), where x is the clr function output. Each list element is named by the sample ID. getFeatures(x) returns the features, getSampleIDs(x) returns sample IDs, and getFeatureNames(x) returns the feature names.

Methods

In the code below, x is an aldex.clr object, and i is a numeric whole number.

getMonteCarloInstances(x): Returns x's Monte Carlo Dirichlet instances.

getSampleIDs(x): Returns the names of the samples. These can be used to access the original reads, as in reads\$sampleID (if the reads are a data frame).

getFeatures(x): Returns the names of the features as a vector.

numFeatures(x): Returns the number of features associated with the data.

numMCInstances(x): Returns the names of the keys that can be used to subset the data rows. The keys values are the rsid's.

getFeatureNames(x): Returns the names of the keys that can be used to subset the data rows. The keys values are the rsid's.

getReads(x): Returns the names of the keys that can be used to subset the data rows. The keys values are the rsid's.

numConditions(x): Returns the names of the keys that can be used to subset the data rows. The keys values are the rsid's.

getMonteCarloReplicate(x, i): Returns the names of the keys that can be used to subset the data rows. The keys values are the rsid's.

Author(s)

Greg Gloor, Ruth Grace Wong, Andrew Fernandes, Jia Rong Wu and Matt Links contributed to this code

References

Please use the citation given by citation(package="ALDEx").

See Also

aldex.clr.function

Examples

    # The 'reads' data.frame or
    # SummarizedExperiment object should have
    # row and column names that are unique,
    # and looks like the following:
    #
    #              T1a T1b  T2  T3  N1  N2  Nx
    #   Gene_00001   0   0   2   0   0   1   0
    #   Gene_00002  20   8  12   5  19  26  14
    #   Gene_00003   3   0   2   0   0   0   1
    #   Gene_00004  75  84 241 149 271 257 188
    #   Gene_00005  10  16   4   0   4  10  10
    #   Gene_00006 129 126 451 223 243 149 209
    #       ... many more rows ...

    data(selex)
    #subset for efficiency
    selex <- selex[1201:1600,]
    conds <- c(rep("NS", 7), rep("S", 7))

    # x is an object of type aldex.clr
    x <- aldex.clr(selex, conds, mc.samples = 2, denom="all", verbose = FALSE)

    # get all of the Monte Carlo Dirochlet instances
    monteCarloInstances <- getMonteCarloInstances(x)

    # get sample names
    sampleIDs <- getSampleIDs(x)

    # get features
    features <- getFeatures(x)

    # get number of features
    numFeatures <- numFeatures(x)

    # get number of Monte Carlo Dirochlet instances
    numInstances <- numMCInstances(x)

    # get names of features
    featureNames <- getFeatureNames(x)

    # get number of conditions
    conditions <- numConditions(x)

    # get number of conditions
    reads <- getReads(x)

    # retrieve the first Monte Carlo Dirochlet instance.
    monteCarloInstance <- getMonteCarloReplicate(x,1)

ALDEx2 documentation built on Nov. 8, 2020, 8:05 p.m.