plot_beta_fcm: Plot function for beta diversity analysis of FCM data
In rprops/Phenoflow_package: Advanced analysis of microbial flow cytometry data

This function visualizes the beta diversity analysis generated by beta_div_fcm()

plot_beta_fcm(
  x,
  color = NA,
  shape = NA,
  labels = c("Factor 1", "Factor 2"),
  legend.pres = NULL
)

`x`	flowbasis object generated by flowBasis()
`color`	A vector of factors indicating the groups to be colored in the plot
`shape`	A vector of factors indicating the shape of the groups in the plot
`labels`	A vector of length 2, giving the labels for color and shape to be used in the legend. Has to be in the order c('color','shape').
`legend.pres`	Surpresses legend when there is no definition of labels.

## Short example

# Load precomputed fingerprint object
data(CoolingTower)

# Calculate diversity values
beta <- beta_div_fcm(CoolingTower,ord.type="PCoA")
plot_beta_fcm(beta)

## Full data processing example

# Load raw data (imported using flowCore)
data(flowData)
# Asinh transform and select parameters of interest (cells were stained with Sybr Green I).
flowData_transformed <- flowCore::transform(flowData,`FL1-H`=asinh(`FL1-H`),
       `SSC-H`=asinh(`SSC-H`), 
       `FL3-H`=asinh(`FL3-H`), 
       `FSC-H`=asinh(`FSC-H`))
param=c('FL1-H', 'FL3-H','SSC-H','FSC-H')
flowData_transformed = flowData_transformed[,param]

# Create a PolygonGate for denoising the dataset
# Define coordinates for gate in sqrcut1 in format: c(x,x,x,x,y,y,y,y)
sqrcut1 <- matrix(c(8.75,8.75,14,14,3,7.5,14,3),ncol=2, nrow=4)
colnames(sqrcut1) <- c('FL1-H','FL3-H')
polyGate1 <- flowCore::polygonGate(.gate=sqrcut1, filterId = 'Total Cells')

# Gating quality check
flowViz::xyplot(`FL3-H` ~ `FL1-H`, data=flowData_transformed[1], filter=polyGate1,
         scales=list(y=list(limits=c(0,14)),
         x=list(limits=c(6,16))),
         axis = lattice::axis.default, nbin=125, 
         par.strip.text=list(col='white', font=2, cex=2), smooth=FALSE)
 
 # Isolate only the cellular information based on the polyGate1
 flowData_transformed <- flowCore::Subset(flowData_transformed, polyGate1)
 
 # Normalize parameter values to [0,1] interval based on max. value across parameters
 summary <- flowCore::fsApply(x=flowData_transformed,FUN=function(x) apply(x,2,max),use.exprs=TRUE)
 max = max(summary[,1])
 mytrans <- function(x) x/max
 flowData_transformed <- flowCore::transform(flowData_transformed,`FL1-H`=mytrans(`FL1-H`),
         `FL3-H`=mytrans(`FL3-H`), 
         `SSC-H`=mytrans(`SSC-H`),
         `FSC-H`=mytrans(`FSC-H`))
 
 # Calculate fingerprint
 fbasis <- flowFDA::flowBasis(flowData_transformed, param, nbin=128, 
         bw=0.01, normalize=function(x) x)
 
 # Calculate diversity
 beta <- beta_div_fcm(fbasis,ord.type="PCoA")
 plot_beta_fcm(beta)