Plot a PARAFAC model

Plot a PARAFAC model

Usage

plotPARAFACmodel(
  model,
  dataset,
  numComponents,
  colourCols = NULL,
  legendTitles = NULL,
  xLabels = NULL,
  legendColNums = NULL,
  arrangeModes = NULL,
  continuousModes = NULL,
  overallTitle = ""
)

Arguments

model

Model output from parafac().

dataset

A longitudinal microbiome dataset, ideally processed with processDataCube(), formatted as follows:

data

Array object of the data cube

mode1

Dataframe with all the subject metadata, 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 array.

numComponents

Number of PARAFAC components in the model.

colourCols

Vector of strings stating which column names should be factorized for colours per mode.

legendTitles

Vector of strings stating the legend title per mode.

xLabels

Vector of strings stating the x-axis labels per mode.

legendColNums

Vector of integers stating the desired number of columns for the legends per mode.

arrangeModes

Vector of boolean values per mode, stating if the loadings should be arranged according to colourCols (TRUE) or not (FALSE).

continuousModes

Vector of boolean values per mode, stating if the loadings should be plotted as a line plot (TRUE) or a bar plot (FALSE).

overallTitle

Overall title of the plot.

Value

Plot object

Examples

library(multiway)
#> Loading required package: CMLS
#> Loading required package: quadprog
#> Loading required package: parallel
#> 
#> Attaching package: ‘multiway’
#> The following objects are masked from ‘package:parafac4microbiome’:
#> 
#>     corcondia, parafac
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:Biostrings’:
#> 
#>     collapse, intersect, setdiff, setequal, union
#> The following object is masked from ‘package:XVector’:
#> 
#>     slice
#> The following object is masked from ‘package:Biobase’:
#> 
#>     combine
#> The following objects are masked from ‘package:GenomicRanges’:
#> 
#>     intersect, setdiff, union
#> The following object is masked from ‘package:GenomeInfoDb’:
#> 
#>     intersect
#> The following objects are masked from ‘package:IRanges’:
#> 
#>     collapse, desc, intersect, setdiff, slice, union
#> The following objects are masked from ‘package:S4Vectors’:
#> 
#>     first, intersect, rename, setdiff, setequal, union
#> The following objects are masked from ‘package:BiocGenerics’:
#> 
#>     combine, intersect, setdiff, union
#> The following object is masked from ‘package:matrixStats’:
#> 
#>     count
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)
set.seed(0)

# Process the data
processedFujita = processDataCube(Fujita2023, sparsityThreshold=0.9, centerMode=1, scaleMode=2)

# Make PARAFAC model
model = parafac(processedFujita$data, nfac=2, nstart=10, verbose=FALSE)

# Make plot
plotPARAFACmodel(model, processedFujita,
  numComponents = 2,
  colourCols = c("", "Genus", ""),
  legendTitles = c("", "Genus", ""),
  xLabels = c("Replicate", "Feature index", "Time point"),
  legendColNums = c(0,5,0),
  arrangeModes = c(FALSE, TRUE, FALSE),
  continuousModes = c(FALSE,FALSE,TRUE),
  overallTitle = "Fujita PARAFAC model")