clr: Centred log-ratio transform
| clr | R Documentation |
Centred log-ratio transform
Description
Transforms readcount-matrix with Aitchisons transform.
Usage
clr(readcount.mat, n.pseudo = 1)
Arguments
readcount.mat |
matrix with readcount data. |
n.pseudo |
number of pseudo-readcounts to add. |
Details
This is a standard implementation of the Aitchisons centered log-ratio transform (Aitchison 1986) for compositional data. Readcount data can be seen as compositional data since the total number of readcounts in a sample does not carry any information about the biology, but is simply an effect of sequencing depth. Thus, the information in the data lies in the relative values, not the absolute. By transforming such data with this function, you get data who are better suited for a number of downstream analyses, e.g. typically analyses making use of sum-of-squares type of statistics, like PCA, PLS, ANOVA or clustering with euclidean distances.
The readcount.mat must have the samples in the rows and the taxa in the
columns. Transpose if necessary.
The transform does not accept zeros in any cell of the readcount.mat. To
cope with this you add pseudo-counts. Bu default 1 additional read is assigned to
all cells in readcount.mat. You may change this value, and it need not
be an integer. The rationale behind this is that we a priori assume a uniform
distribution of the taxa, and the more pseudo-counts you add, the more weight
you give to this prior.
Value
A matrix of same size as the input, but with transformed readcounts.
Author(s)
Lars Snipen.
References
Aitchison J. The Statistical Analysis of Compositional Data. London, UK: Chapman & Hall; 1986.
