addStepwiseDivergence: Beta diversity between consecutive time steps

In microbiome/miaTime: Microbiome Time Series Analysis

Beta diversity between consecutive time steps

Description

Calculates sample dissimilarity between consecutive time points along with time difference.

Usage

getStepwiseDivergence(x, ...)

addStepwiseDivergence(x, ...)

## S4 method for signature 'ANY'
getStepwiseDivergence(
  x,
  time.col,
  assay.type = "counts",
  time.interval = 1L,
  group = NULL,
  method = "bray",
  ...
)

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

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")
time.interval	Integer scalar. Indicates the increment between time steps. By default, the function compares each sample to the previous one. If you need to take every second, every third, or so, time step, then increase this accordingly. (Default: 1L)
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 scalar. Specifies a column name for storing divergence results. (Default: "divergence")
name.time	Character scalar. Specifies a column name for storing time differences. (Default: "time_diff")

Details

These functions calculate time-wise divergence, meaning each sample is compared to the previous i-th sample, where i is the specified time interval (see time.interval). By default, the function calculates divergence by comparing all samples with each other. However, it is often more meaningful to calculate divergence within a specific patient or group (see the group parameter).

Value

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

See Also

mia::addDivergence()

Examples

library(miaTime)

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

# Calculate divergence
tse <- addStepwiseDivergence(
    tse,
    group = "subject",
    time.interval = 1,
    time.col = "time",
    assay.type = "relabundance"
    )

microbiome/miaTime documentation built on Nov. 4, 2024, 10:23 p.m.