findClusters {Biopeak} | R Documentation |
The findClusters function estimates the number of genes with similar temporal regulation and supports three different clustering algorithms: kmeans, dbscan and hierarchical clustering. Clustering is based on a PCA projection of the input data.
findClusters(peakdet, exprmat, maxclusters = 3, eps = 0.02, clusters = 3, method = "kmeans")
peakdet |
A list returned by the peakDetection function. |
exprmat |
A numeric matrix with expression series data with variables as rownames. |
maxclusters |
Maximal number of clusters used for kmeans cluster estimation. |
eps |
Epsilon value used by the dbscan algorithm. |
clusters |
Number of clusters used for the cutree function of the hierarchical clustering. |
method |
A character string defining the clustering algorithm with options: c('kmeans', 'dbscan', 'hclust'). |
Returns a cluster assignment of each variable and the number of identified clusters.
David Lauenstein
# Example based on the heat-shock dataset data(heat) heat = as.matrix(heat) # Define series series <- c(37,40,41,42,43) # Run the peak detection algorithm peakdet <- peakDetection(heat, series, type ='rnaseq', actstrength = 1.5, prominence = 1.3, minexpr = 5000) # Cluster exploration using kmeans with a maximum of 4 clusters to be assigned clusters <- findClusters(peakdet, heat, maxclusters = 4, method = 'kmeans')