Calculate purity
Calculates purity for liger clustering and external clustering (true clusters/classes).
Purity can sometimes be a more useful metric when the clustering to be tested contains more
subgroups or clusters than the true clusters (or classes). Purity also ranges from 0 to 1,
with a score of 1 representing a pure, or accurate, clustering.
calcPurity(object, classes.compare, verbose = TRUE)
object |
|
classes.compare |
Clustering with which to compare (named vector). |
verbose |
Print messages (TRUE by default) |
Purity value.
## Not run:
# ligerex (liger object), factorization complete
ligerex <- quantile_norm(ligerex)
# toy clusters
cluster1 <- sample(c('type1', 'type2', 'type3'), ncol(ligerex@raw.data[[1]]), replace = TRUE)
names(cluster1) <- colnames(ligerex@raw.data[[1]])
cluster2 <- sample(c('type4', 'type5', 'type6'), ncol(ligerex@raw.data[[2]]), replace = TRUE)
names(cluster2) <- colnames(ligerex@raw.data[[2]])
# get ARI for first clustering
ari1 <- calcPurity(ligerex, cluster1)
# get ARI for second clustering
ari2 <- calcPurity(ligerex, cluster2)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.