highDimensionARI: Calculate ARI for high-dimensional data via data splits

Description Usage Arguments Value Author(s) References

Description

This function is used to calculate Adjusted Rand Index (ARI) values for high-dimensional data.

Usage

1
highDimensionARI(x, y, splits = 2, verbose = FALSE) 

Arguments

x

Vector of classification labels

y

Vector of classification labels

splits

Number of subsets data should be split into

verbose

TRUE if verbose output is desired

Value

Value of Adjusted Rand Index for samples x and y

Author(s)

Andrea Rau <andrea.rau@jouy.inra.fr>

References

Rau, A., Maugis-Rabusseau, C., Martin-Magniette, M.-L., Celeux G. (2015). Co-expression analysis of high-throughput transcriptome sequencing data with Poisson mixture models. Bioinformatics, 31(9):1420-1427.

Rau, A., Celeux, G., Martin-Magniette, M.-L., Maugis-Rabusseau, C. (2011). Clustering high-throughput sequencing data with Poisson mixture models. Inria Research Report 7786. Available at http://hal.inria.fr/inria-00638082.


HTSCluster documentation built on May 2, 2019, 2:41 a.m.