CellMigPCAclust {cellmigRation} | R Documentation |
The CellMigPCAclust function automatically generates clusters based on the Principal Component Analysis.
CellMigPCAclust( object, parameters = c(1, 2, 3), export = FALSE, interactive = TRUE )
object |
|
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 |
PCA Graph of cells and PCA Graph of variables.
Salim Ghannoum salim.ghannoum@medisin.uio.no
https://www.data-pulse.com/dev_site/cellmigration/
## 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))