get.cluster.names | R Documentation |
get.cluster.names
uses predefined marker genes to assign clusters with
putative cell type or state labels.
set.cluster.names
saves the cluster names in storage and in the environment
object
get.cluster.names(environment, types, min.fold = 1.25, max.Qval = 0.1,
print = T)
set.cluster.names(environment, names)
environment |
|
types |
data frame associating cell type or state with marker genes |
min.fold |
minimum fold change to consider a marker as overexpressed |
max.Qval |
maximum FDR q value to consider a marker as overexpressed |
print |
whether to print output calculations |
names |
cluster names defined in get.cluster.names |
get.cluster.names
returns a vector containing assigned cluster
name labels
set.cluster.names
returns an environment
object coded
with cluster names
set.cluster.names
: set annotations to clusters
LCMV1 <- setup_LCMV_example()
LCMV1 <- get.variable.genes(LCMV1, min.mean = 0.1, min.frac.cells = 0,
min.dispersion.scaled = 0.1)
LCMV1 <- PCA(LCMV1)
LCMV1 <- cluster.analysis(LCMV1)
types = rbind(
data.frame(type='Tfh',gene=c('Tcf7','Cxcr5','Bcl6')),
data.frame(type='Th1',gene=c('Cxcr6','Ifng','Tbx21')),
data.frame(type='Tcmp',gene=c('Ccr7','Bcl2','Tcf7')),
data.frame(type='Treg',gene=c('Foxp3','Il2ra')),
data.frame(type='Tmem',gene=c('Il7r','Ccr7')),
data.frame(type='CD8',gene=c('Cd8a')),
data.frame(type='CD4', gene = c("Cd4")),
data.frame(type='Cycle',gene=c('Mki67','Top2a','Birc5'))
)
summarize(LCMV1)
cluster_names <- get.cluster.names(LCMV1, types, min.fold = 1.0, max.Qval = 0.01)
LCMV1 <- set.cluster.names(LCMV1, names = cluster_names)
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