DianaClustering: DianaClustering:

In nathansam/CircadianTools: Collection of Tools for Detecting Rhythmic Genes

Description

Applies DIANA (DIvisive ANAlysis) clustering to a transcriptomics dataset and appends a cluster column to this dataset for all genes.

Usage

DianaClustering(
  dataset = NULL,
  distance = NULL,
  k = 10,
  metric = "euclidean",
  nthreads = NULL,
  scale = TRUE,
  center = TRUE
)

Arguments

dataset	A transcriptomics dataset. First columns should be gene names. All other columns should be expression levels. Not needed if an argument to distance is given.
distance	A distance matrix. If a distance matrix has already been created (such as by using the DistanceGen function), the matrix can be passed to this function to save time. If a distance matrix is not provided then it will be generated by the function.
k	The total number of clusters.
metric	The distance metric to be used to calculate the distances between genes. See parallelDist::parDist for all accepted arguments. Also allows the option of 'abs.correlation'. Not used if a distance matrix is provided.
nthreads	Number of processor threads to be used for calculating the distance matrix. If not specifed then the maximum number of logical cores are used.
scale	Logical. If TRUE then each gene will be scaled
center	If the gene activity should be centered before clustering.

Value

Returns transcriptomics dataset provided with additional cluster column appended denoted which cluster each gene belongs to.

Examples

t.filter <-TFilter(Laurasmappings, nthreads = 2)
diana.df <- DianaClustering(t.filter, k= 10, nthreads = 2)

nathansam/CircadianTools documentation built on Dec. 26, 2019, 11:30 a.m.