Description Usage Arguments Value Author(s) References Examples
View source: R/all_functions_v8.R
The CellMigPCAclust function automatically generates clusters based on the Principal Component Analysis.
1 2 3 4 5 6 | 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/
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## 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))
|
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