Description Usage Arguments Details Value References Examples
View source: R/correlation_filtering_clustering.R
Runs consensus hierarchical clustering on PCA feature space of scExp object. Plot consensus scores for each number of clusters. See ConsensusClusterPlus - Wilkerson, M.D., Hayes, D.N. (2010). ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics, 2010 Jun 15;26(12):1572-3.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | consensus_clustering_scExp(
scExp,
prefix = NULL,
maxK = 10,
reps = 100,
pItem = 0.8,
pFeature = 1,
distance = "pearson",
clusterAlg = "hc",
innerLinkage = "ward.D",
finalLinkage = "ward.D",
plot_consclust = "pdf",
plot_icl = "png"
)
|
scExp |
A SingleCellExperiment object containing 'PCA' in reducedDims. |
prefix |
character value for output directory. Directory is created only if plot_consclust is not NULL. This title can be an abosulte or relative path. |
maxK |
integer value. maximum cluster number to evaluate. (10) |
reps |
integer value. number of subsamples. (100) |
pItem |
numerical value. proportion of items to sample. (0.8) |
pFeature |
numerical value. proportion of features to sample. (1) |
distance |
character value. 'pearson': (1 - Pearson correlation), 'spearman' (1 - Spearman correlation), 'euclidean', 'binary', 'maximum', 'canberra', 'minkowski' or custom distance function. ('pearson') |
clusterAlg |
character value. cluster algorithm. 'hc' heirarchical (hclust), 'pam' for paritioning around medoids, 'km' for k-means upon data matrix, 'kmdist' ('hc') for k-means upon distance matrices (former km option), or a function that returns a clustering. ('hc') |
innerLinkage |
hierarchical linkage method for subsampling. ('ward.D') |
finalLinkage |
hierarchical linkage method for consensus matrix. ('ward.D') |
plot_consclust |
character value. NULL - print to screen, 'pdf', 'png', 'pngBMP' for bitmap png, helpful for large datasets. ('pdf') |
plot_icl |
same as above for item consensus plot. ('png') |
This functions takes as input a SingleCellExperiment object that must have 'PCA' in reducedDims and outputs a SingleCellExperiment object containing consclust list calculated cluster consensus and item consensus scores in metadata.
Returns a SingleCellExperiment object containing consclust list, calculated cluster consensus and item consensus scores in metadata.
ConsensusClusterPlus package by Wilkerson, M.D., Hayes, D.N. (2010). ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics, 2010 Jun 15;26(12):1572-3.
1 2 3 | data("scExp")
scExp_cf = correlation_and_hierarchical_clust_scExp(scExp)
scExp_cf = consensus_clustering_scExp(scExp)
|
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