Matrix Spectral Decomposition (matSpD) - estimate the equivalent number of independent variables in a correlation (r) matrix.

Analogous to my SNPSpD approach, matSpD provides a measure of the equivalent number of independent variables in a correlation (r) matrix, by examining the ratio of observed eigenvalue variance (after spectral decomposiiton) to its theoretical maximum. Please refer to the SNPSpD webpage for further information.

It is worth noting that although the SNPSpD approach utilises an LD correlation measure which is not technically appropriate for SNPs, which are multinomial (categorical/ordinal) variables, I've found the results comparable to using Spearman's rho. Indeed, it is generally accepted that use of Pearson's correlation (r) [appropriate for interval/numerical data] on categorical/ordinal data, rarely affects substantive research conclusions. Nonetheless, one may wish to upload their preferred matrix of correlations using this interface.
 

The matSpD interface takes one file as input [please use short simple file names (i.e., no spaces or special characters)]:
1) a space or tab delimited ascii (ansi) text file containing your correlation (r) matrix ("corr.matrix").

The following links provide an example of such an input file and its corresponding output:
corr.matrix - input file,
results - output file.