Reorganize longitudinal microbiome into a data cube ready for PARAFAC modelling.

Usage

reshapeData(
  Xlong,
  subjectMetadata,
  featureMetadata,
  timepointMetadata,
  timepointOrder = sort(unique(timepointMetadata))
)

Arguments

Xlong: Longitudinal microbiome count data in matrix (long) format.
subjectMetadata: Vector containing the subjects corresponding to the measurements in Xlong.
featureMetadata: Taxonomic classification of the microbiota, ordered the same as the columns in Xlong.
timepointMetadata: Vector containing the time points corresponding to the measurements in Xlong.
timepointOrder: Vector containing the required order of the timepoints in timepointMetadata (default: sort(unique(timepointMetadata)) ).

Value

#' A list object containing

data: Array object of the data cube
mode1: Dataframe with the subjects, ordered the same as the rows in the data cube.
mode2: Taxonomic classification of the microbiota, ordered the same as the columns in the data cube.
mode3: Dataframe with the time metadata, ordered the same as the third dimension in the data cube.

Examples

library(dplyr)

Xlong = array(rnorm(108*5*10), c(108*5, 10))
subjects = rep(1:108, 5)
features = rep(1:10)
timepoints = rep(1:5, each=108)

dataset = reshapeData(Xlong, subjects, features, timepoints)