CellMigPCAclust: PCA Clusters

In ocbe-uio/CellMigRation: Track Cells, Analyze Cell Trajectories and Compute Migration Statistics

Description

The CellMigPCAclust function automatically generates clusters based on the Principal Component Analysis.

Usage

CellMigPCAclust(
  object,
  parameters = c(1, 2, 3),
  export = FALSE,
  interactive = TRUE
)

Arguments

object	CellMig class object, which is a list of data frames resulted from the PreProcessing.
parameters	A numeric vector contains the parameters to be included in the Principal Component Analysis. These numbers can be obtained from the outcome of the FinRes() function.
export	if 'TRUE' (default), exports function output to CSV file
interactive	logical, shall the PCA analysis be generated in a interactive fashion

Value

PCA Graph of cells and PCA Graph of variables.

Author(s)

Salim Ghannoum [e-mail]

References

https://www.data-pulse.com/dev_site/cellmigration/

Examples

## The analysis only supports the interactive method!
## If interactive=FALSE, the function will return NULL
data(WSADataset)
wasDF <- WSADataset[seq(1, 300, by=1), ]
wsaTD <- CellMig(wasDF)
CellMigPCAclust(wsaTD, parameters=c(1,9), interactive=FALSE)
##
## A real world example is shown below (uncomment)
# data(WSADataset)
# wasDF <- WSADataset[seq(1,300,by=1),]
# wsaTD <- CellMig(wasDF)
# wsaTD <- wsaPreProcessing(wsaTD,FrameN=55)
# wsaTD <-FMI(wsaTD,TimeInterval=10)
# wsaTD <-ForwardMigration(wsaTD,TimeInterval=10)
# wsaTD <-FinRes(wsaTD,ParCor=FALSE)
# PCAclust <- CellMigPCAclust(wsaTD,parameters=c(1,9))

ocbe-uio/CellMigRation documentation built on Dec. 26, 2021, 10:19 p.m.