R implementation of the PhenoGraph algorithm
Rphenograph(data, k = 30)a list contains an igraph graph object for graph_from_data_frame and a communities object, the operations of this class contains:
returns the communities object itself, invisibly.
returns an integer scalar.
returns a numeric vector.
returns a numeric vector, one number for each vertex in the graph that was the input of the community detection.
returns a numeric scalar.
returns a character scalar.
returns a logical vector.
returns a logical scalar.
returns a two-column numeric matrix.
returns a numeric vector, the membership vector of the vertices.
returns a dendrogram object.
returns a character vector.
returns a numeric scalar for communities found with the InfoMAP method and NULL for other methods.
for communities objects returns NULL, invisibly.
matrix; input data matrix
integer; number of nearest neighbours (default:30)
A simple R implementation of the [PhenoGraph](http://www.cell.com/cell/abstract/S0092-8674(15)00637-6) algorithm, which is a clustering method designed for high-dimensional single-cell data analysis. It works by creating a graph ("network") representing phenotypic similarities between cells by calclating the Jaccard coefficient between nearest-neighbor sets, and then identifying communities using the well known [Louvain method](https://sites.google.com/site/findcommunities/) in this graph.
Jacob H. Levine and et.al. Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis. Cell, 2015.