clust.dist: Computes distances on a data matrix
In EMA: Easy Microarray Data Analysis

Description Usage Arguments Details Value Author(s) See Also

Computes distances between the columns of an expression matrix using the specified distance measure.

1	clust.dist(mat, meth.dis="euclidean")

`mat`	Expression matrix, genes on rows and samples on columns
`meth.dis`	Character string specifying the distance measure to be used. This must be one of 'euclidean', 'manhattan', 'pearson', 'pearsonabs', 'spearman', 'spearmanabs', 'jaccard', 'dice'

Available distance measures are (written for two vectors x and y):

'euclidean' : Usual square distance between the two vectors.
'manhattan' : Absolute distance between the two vectors
'pearson' : Pearson correlation distance. (1 - r)/2
'pearsonabs' : Absolute Pearson correlation distance. 1 - abs(r)
'spearman' : Spearman rank correlation distance. (1 - r)/2
'spearmanabs' : Absolute Spearlan rnak correlation distance. 1 - abs(r)
'jaccard' : Jaccard distance on 0-1 matrix
'dice': Dice distance on 0-1 matrix

A distance matrix.

Nicolas Servant, Eleonore Gravier, Pierre Gestraud, Cecile Laurent, Caroline Paccard, Anne Biton, Jonas Mandel, Bernard Asselain, Emmanuel Barillot, Philippe Hupe

jaccard,dice,daisy

EMA documentation built on March 26, 2020, 8:40 p.m.