% Generated by roxygen2: do not edit by hand % Please edit documentation in R/runCluster.R \name{runScranSNN} \alias{runScranSNN} \title{Get clustering with SNN graph} \usage{ runScranSNN( inSCE, useReducedDim = "PCA", useAssay = NULL, useAltExp = NULL, altExpAssay = "counts", altExpRedDim = NULL, clusterName = "cluster", k = 14, nComp = 10, weightType = "jaccard", algorithm = c("louvain", "leiden", "walktrap", "infomap", "fastGreedy", "labelProp", "leadingEigen"), BPPARAM = BiocParallel::SerialParam(), seed = 12345, ... ) } \arguments{ \item{inSCE}{A \linkS4class{SingleCellExperiment} object.} \item{useReducedDim}{A single \code{character}, specifying which low-dimension representation (\code{\link{reducedDim}}) to perform the clustering algorithm on. Default \code{"PCA"}.} \item{useAssay}{A single \code{character}, specifying which \code{\link{assay}} to perform the clustering algorithm on. Default \code{NULL}.} \item{useAltExp}{A single \code{character}, specifying the assay which \code{\link{altExp}} to perform the clustering algorithm on. Default \code{NULL}.} \item{altExpAssay}{A single \code{character}, specifying which \code{\link{assay}} in the chosen \code{\link{altExp}} to work on. Only used when \code{useAltExp} is set. Default \code{"counts"}.} \item{altExpRedDim}{A single \code{character}, specifying which \code{\link{reducedDim}} within the \code{\link{altExp}} specified by \code{useAltExp} to use. Only used when \code{useAltExp} is set. Default \code{NULL}.} \item{clusterName}{A single \code{character}, specifying the name to store the cluster label in \code{\link{colData}}. Default \code{"cluster"}.} \item{k}{An \code{integer}, the number of nearest neighbors used to construct the graph. Smaller value indicates higher resolution and larger number of clusters. Default \code{14}.} \item{nComp}{An \code{integer}. The number of components to use for graph construction. Default \code{10}. See Detail.} \item{weightType}{A single \code{character}, that specifies the edge weighing scheme when constructing the Shared Nearest-Neighbor (SNN) graph. Choose from \code{"rank"}, \code{"number"}, \code{"jaccard"}. Default \code{"jaccard"}.} \item{algorithm}{A single \code{character}, that specifies the community detection algorithm to work on the SNN graph. Choose from \code{"leiden"}, \code{"louvain"}, \code{"walktrap"}, \code{"infomap"}, \code{"fastGreedy"}, \code{"labelProp"}, \code{"leadingEigen"}. Default \code{"louvain"}. See Detail.} \item{BPPARAM}{A \code{\link[BiocParallel]{BiocParallelParam}} object to use for processing the SNN graph generation step in parallel.} \item{seed}{Random seed for reproducibility of results. Default \code{NULL} will use global seed in use by the R environment.} \item{...}{Other optional parameters passed to the \code{\link{igraph}} clustering functions. See Details.} } \value{ The input \linkS4class{SingleCellExperiment} object with \code{factor} cluster labeling updated in \code{colData(inSCE)[[clusterName]]}. } \description{ Perform SNN graph clustering on a \linkS4class{SingleCellExperiment} object, with graph construction by \code{\link[scran]{buildSNNGraph}} and graph clustering by "igraph" package. } \details{ Different graph based clustering algorithms have diverse sets of parameters that users can tweak. The help information can be found here: \itemize{ \item{for \code{"louvain"}, see function help \code{\link[igraph]{cluster_louvain}}} \item{for \code{"leiden"}, see function help \code{\link[igraph]{cluster_leiden}}} \item{for \code{"walktrap"}, see function help \code{\link[igraph]{cluster_walktrap}}} \item{for \code{"infomap"}, see function help \code{\link[igraph]{cluster_infomap}}} \item{for \code{"fastGreedy"}, see function help \code{\link[igraph]{cluster_fast_greedy}}} \item{for \code{"labelProp"}, see function help \code{\link[igraph]{cluster_label_prop}}} \item{for \code{"leadingEigen"}, see function help \code{\link[igraph]{cluster_leading_eigen}}} } The Scran SNN building method can work on specified \code{nComp} components. When users specify input matrix by \code{useAssay} or \code{useAltExp} + \code{altExpAssay}, the method will generate \code{nComp} components and use them all. When specifying \code{useReducedDim} or \code{useAltExp} + \code{altExpRedDim}, this function will subset the top \code{nComp} components and pass them to the method. } \examples{ data("mouseBrainSubsetSCE") mouseBrainSubsetSCE <- runScranSNN(mouseBrainSubsetSCE, useReducedDim = "PCA_logcounts") } \references{ Aaron Lun and et. al., 2016 }