The SPADEResults object is a S4 object containing cell clustering results.
This object mainly stores the cluster abundance matrix (i.e. the number of cells associated to each sample for each cluster) and the cluster phenotypes matrix (i.e. the median expressions for each marker of each cluster).
In addition, this object can contain information about clustering results, such a SPADE tree.
The 'cluster.abundances' dataframe contains the number of cells associated to each sample for each cluster. This dataframe stores the clusters in rows and the samples in columns.
The 'cluster.phenotypes' dataframe stores the median expressions for each marker of each cluster. This dataframe stores in the first column the sample names, in the second column the cluster names, and in the others columns the maker median expressions.
The 'bounds' dataframe contains the marker expressions boundaries (minimum and maximum, or specific percentiles) for each marker.
The 'print()' and 'show()' can be used to display a summary of this object.
cluster.abundancesa dataframe containing the number of cells associated to each sample for each cluster
cluster.phenotypesa dataframe containing the median expressions for each marker of each cluster
sample.namesa character vector containing the sample names
cluster.namesa character vector containing the cluster names
cluster.numbera numeric specifying the number of clusters
marker.namesa character vector containing the marker names
clustering.markersa character vector specifying the markers that have been used by the clustering algorithms
boundsa numeric data.frame containing the marker expressions boundaries for each marker
use.raw.mediansa logical specifying if the marker expressions correspond to raw or transformed data
flowseta flowSet object containing the imported SPADE FCS files
fcs.filesa character vector containing the location of the imported FCS files
grapha igraph object containing the SPADE tree structure
graph.layouta numeric matrix containing the SPADE tree layout
assignmentsa dataframe containing annotations for each sample samples such as a biological condition ("bc"), a timepoint condition ("tp") or an individual ("ind") assignment
th.min_cellsa numeric specifying the minimal number of cells that a cluster for a given samples needs to have to be taken into consideration in its phenotypical characterization
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