Containerizing IMC data into the SummarizedExperiment class, this container inherits packages from FlowSOM and diffcyt to compute clusters and test for differential abundance or state heterogeneity. Creating a flowSet is cumbersome, so we can stream-line into a summarized experiment into a quick and fast way to detect changes in cell populations.
library(CATALYST)
library(diffcyt)
library(imcExperiment)
data(imcdata)
head(rownames(imcdata))
imcData<-imcdata
# for plot scatter to work need to set the rowData feature in a specific way.
channel<-sapply(strsplit(rownames(imcData),"_"),function(x) x[3])
channel[34:35]<-c("Ir1911","Ir1931")
marker<-sapply(strsplit(rownames(imcData),"_"),function(x) x[2])
rowData(imcData)<-DataFrame(channel_name=channel,marker_name=marker)
rownames(imcData)<-marker
plotScatter(imcData,rownames(imcData)[17:18],assay='counts')
# convert to flowSet
## the warning has to do with duplicated Iridium channels.
(fsimc <- sce2fcs(imcData, split_by = "ROIID"))
## now we have a flowSet.
pData(fsimc)
fsApply(fsimc,nrow)
dim(exprs(fsimc[[1]]))
exprs(fsimc[[1]])[1:5,1:5]
## set up the metadata files.
head(marker_info)
exper_info<-data.frame(group_id=colData(imcData)$Treatment[match(pData(fsimc)$name,
colData(imcData)$ROIID)],
patient_id=colData(imcData)$Patient.Number[match(pData(fsimc)$name,
colData(imcData)$ROIID)],
sample_id=pData(fsimc)$name)
## create design
design<-createDesignMatrix(
exper_info,cols_design=c("group_id","patient_id"))
##set up contrast
contrast<-createContrast(c(0,1,0))
nrow(contrast)==ncol(design)
data.frame(parameters=colnames(design),contrast)
## flowSet to DiffCyt
out_DA<-diffcyt(
d_input=fsimc,
experiment_info=exper_info,
marker_info=marker_info,
design=design,
contrast=contrast,
analysis_type = "DA",
seed_clustering = 123
)
topTable(out_DA,format_vals = TRUE)
out_DS<-diffcyt(
d_input=fsimc,
experiment_info=exper_info,
marker_info=marker_info,
design=design,
contrast=contrast,
analysis_type='DS',
seed_clustering = 123,
plot=FALSE)
topTable(out_DS,format_vals = TRUE)