Relabel cluster labels across parameter runs to maximise their similarity.

Relabel cluster labels across parameter runs to maximise their similarity.

connectClusters(se, map_to = NULL, verbose = TRUE)

Arguments

se

A SpatialExperiment, SingleCellExperiment or SummarizedExperiment object with cluster labels in colData(se).

map_to

A string scalar specify a cluster to map to.

verbose

A logical scalar specifying verbosity.

Value

A SpatialExperiment / SingleCellExperiment / SummarizedExperiment object with 'connected' cluster labels in colData(se).

Examples

data(rings)
spe <- runBanksyPCA(rings, assay_name = "counts", lambda = c(0, 0.2), npcs = 20)
#> Computing neighbors...
#> Spatial mode is kNN_median
#> Parameters: k_geom=15
#> Done
#> --- lambda = 0 ---
#> Building sparse weight matrix
#> Computing scaling parameters for own expression
#> Computing clipping excess for own expression
#> Computing scaling params and clipping for H0
#> H0 genes requiring clipping: 0 / 50
#> Clipping corrections: own=0 H0=0 entries
#> Computing BANKSY PCA (20 PCs) via C++ irlba (work=27)
#>   iter=1  mprod=54  sv[20]=1.2308e+01  t=0s
#>   iter=2  mprod=68  sv[20]=1.4545e+01  t=0s
#>   iter=5  mprod=110  sv[20]=1.5989e+01  t=0s
#>   Converged: iter=5, mprod=110
#> --- lambda = 0.2 ---
#> Building sparse weight matrix
#> Computing scaling parameters for own expression
#> Computing clipping excess for own expression
#> Computing scaling params and clipping for H0
#> H0 genes requiring clipping: 0 / 50
#> Clipping corrections: own=0 H0=0 entries
#> Computing BANKSY PCA (20 PCs) via C++ irlba (work=27)
#>   iter=1  mprod=54  sv[20]=8.5000e+00  t=0s
#>   iter=2  mprod=68  sv[20]=1.1893e+01  t=0s
#>   iter=5  mprod=110  sv[20]=1.4406e+01  t=0s
#>   iter=8  mprod=152  sv[20]=1.4489e+01  t=0s
#>   Converged: iter=8, mprod=152
#> Done.
spe <- clusterBanksy(spe, lambda = c(0, 0.2), resolution = 1)
spe <- connectClusters(spe)
#> clust_M0_lam0_k50_res1 --> cluster
#> clust_M0_lam0.2_k50_res1 --> clust_M0_lam0_k50_res1