addDivergence: Estimate divergence

In microbiome/mia: Microbiome analysis

Estimate divergence

Description

Estimate divergence against a given reference sample.

Usage

addDivergence(x, name = "divergence", ...)

## S4 method for signature 'SummarizedExperiment'
addDivergence(x, name = "divergence", ...)

getDivergence(
  x,
  assay.type = assay_name,
  assay_name = "counts",
  reference = "median",
  method = "bray",
  ...
)

## S4 method for signature 'SummarizedExperiment'
getDivergence(
  x,
  assay.type = assay_name,
  assay_name = "counts",
  reference = "median",
  method = "bray",
  ...
)

Arguments

x	a SummarizedExperiment object.
name	Character scalar. The name to be used to store the result in metadata of the output. (Default: method)
...	optional arguments passed to addDissimilarity. Additionally: dimred: Character scalar. Specifies the name of dimension reduction result from reducedDim(x). If used, these values are used to calculate divergence instead of the assay. Can be disabled with NULL. (Default: NULL)
assay.type	Character scalar. Specifies which assay to use for calculation. (Default: "counts")
assay_name	Deprecated. Use assay.type instead.
reference	Character scalar. A column name from colData(x) or either "mean" or "median". (Default: "median")
method	Character scalar. Specifies which dissimilarity to calculate. (Default: "bray")

Details

Microbiota divergence (heterogeneity / spread) within a given sample set can be quantified by the average sample dissimilarity or beta diversity with respect to a given reference sample.

The calculation makes use of the function getDissimilarity(). The divergence measure is sensitive to sample size. Subsampling or bootstrapping can be applied to equalize sample sizes between comparisons.

Value

x with additional colData named name

See Also

• addAlpha

• addDissimilarity

• plotColData

Examples

data(GlobalPatterns)
tse <- GlobalPatterns

# By default, reference is median of all samples. The name of column where
# results is "divergence" by default, but it can be specified. 
tse <- addDivergence(tse)

# The method that are used to calculate distance in divergence and 
# reference can be specified. Here, euclidean distance is used. Reference is
# the first sample. It is recommended # to add reference to colData.
tse[["reference"]] <- rep(colnames(tse)[[1]], ncol(tse))
tse <- addDivergence(
    tse, name = "divergence_first_sample", 
    reference = "reference",
    method = "euclidean")

# Here we compare samples to global mean
tse <- addDivergence(tse, name = "divergence_average", reference = "mean")

# All three divergence results are stored in colData.
colData(tse)

microbiome/mia documentation built on Nov. 20, 2024, 1:12 a.m.