cytof_progression {cytofkit} | R Documentation |
Infer the progression based on the relationship of cell subsets estimated using ISOMAP or Diffusion map.
cytof_progression(data, cluster, method = c("diffusionmap", "isomap", "NULL"), distMethod = "euclidean", out_dim = 2, clusterSampleMethod = c("ceil", "all", "fixed", "min"), clusterSampleSize = 500, sampleSeed = 123)
data |
Expression data matrix. |
cluster |
A vector of cluster results for the data. |
method |
Method for estimation of cell progression, isomap or diffusionmap. |
distMethod |
Method for distance calculation, default is "euclidean", other choices like "manhattan", "cosine", "rankcor". |
out_dim |
Number of transformed dimensions choosen for output. |
clusterSampleMethod |
Cluster sampling method including |
clusterSampleSize |
The number of cells to be sampled from each cluster. |
sampleSeed |
The seed for random down sample of the clusters. |
a list. Includes: sampleData, sampleCluster and progressionData.
d<-system.file('extdata', package='cytofkit') fcsFile <- list.files(d, pattern='.fcs$', full=TRUE) parameters <- list.files(d, pattern='.txt$', full=TRUE) markers <- as.character(read.table(parameters, header = TRUE)[, 1]) xdata <- cytof_exprsMerge(fcsFile, mergeMethod = 'fixed', fixedNum = 2000) clusters <- cytof_cluster(xdata = xdata, method = "Rphenograph") prog <- cytof_progression(data = xdata, cluster = clusters, clusterSampleSize = 100) d <- as.data.frame(cbind(prog$progressionData, cluster = factor(prog$sampleCluster))) cytof_clusterPlot(data =d, xlab = "diffusionmap_1", ylab="diffusionmap_2", cluster = "cluster", sampleLabel = FALSE)