Beta diversity between the baseline and later time steps

Calculates sample dissimilarity between the given baseline and other time points, optionally within a group (subject, reaction chamber, or similar). The corresponding time difference is returned as well.

getBaselineDivergence(x, ...)

addBaselineDivergence(x, ...)

# S4 method for class 'SummarizedExperiment'
getBaselineDivergence(
  x,
  time.col,
  assay.type = "counts",
  reference = NULL,
  group = NULL,
  method = "bray",
  ...
)

# S4 method for class 'SummarizedExperiment'
addBaselineDivergence(
  x,
  name = c("divergence", "time_diff", "ref_samples"),
  ...
)

Arguments

x

A SummarizedExperiment object.

...

Optional arguments passed into mia::addDivergence().

time.col

Character scalar. Specifies a name of the column from colData that identifies the sampling time points for the samples.

assay.type

Character scalar. Specifies which assay values are used in the dissimilarity estimation. (Default: "counts")

reference

Character scalar. Specifies a name of the column from colData that identifies the baseline samples to be used. (Default: NULL)

group

Character scalar. Specifies a name of the column from colData that identifies the grouping of the samples. (Default: NULL)

method

Character scalar. Used to calculate the dissimilarity Method is passed to the function that is specified by dis.fun. (Default: "bray")

name

Character vector. Specifies a column name for storing divergence results. (Default: c("divergence", "time_diff", "ref_samples"))

Value

getBaselineDivergence returns DataFrame object containing the sample dissimilarity and corresponding time difference between samples. addBaselineDivergence, on the other hand, returns a SummarizedExperiment object with these results in its colData.

Details

The group argument allows calculating divergence per group. If given, the divergence is calculated per group. e.g. subject, chamber, group etc. Otherwise, this is done across all samples at once.

The baseline sample(s) always need to belong to the data object i.e. they can be merged into it before applying this function. The reason is that they need to have comparable sample data, at least some time point information for calculating time differences w.r.t. baseline sample.

The baseline time point is by default defined as the smallest time point (per group). Alternatively, the user can provide the baseline vector, or a list of baseline vectors per group (named list per group).

See also

mia::addDivergence()

Examples

library(miaTime)
library(mia)

data(hitchip1006)
tse <- transformAssay(hitchip1006, method = "relabundance")

# By default, reference samples are the samples from the first timepoint
tse <- addBaselineDivergence(
    tse,
    group = "subject",
    time.col = "time",
    assay.type = "relabundance",
    method = "bray")

# Add reference samples to colData, if you want to specify reference
# samples manually
colData(tse)[["reference"]] <- "Sample-875"
tse <- addBaselineDivergence(
    tse,
    reference = "reference",
    group = "subject",
    time.col = "time",
    name = c("divergence_from_baseline", 
        "time_from_baseline", "reference_samples"),
    assay.type = "relabundance",
    method = "bray")