Matrix Spectral Decomposition (matSpD) - estimate the equivalent number of independent variables in a correlation (r) matrix.
Users may also be interested in the leaner version of matSpD, (matSpDlite) which ONLY calculates Veff and VeffLi (i.e., does not perform time-consuming varimax/promax rotations) thus allowing users to obtain Veff/VeffLi values for large numbers (1000s) of variables.
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.
Cheverud JM (2001) A simple correction for multiple comparisons in interval mapping genome scans. Heredity 87:52-8
Li J, Ji L (2005) Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 95:221-227
Nyholt DR (2004) A simple correction for multiple testing for SNPs in linkage disequilibrium with each other. Am J Hum Genet 74(4):765-769.
R Development Core Team (2003) R: a language
and environment for statistical computing. R Foundation for Statistical
Computing, Vienna, http://www.R-project.org
(accessed March 1, 2004)
Page last updated August 10, 2005.
Special thanks to David Smyth (Genepi's
IT guru) for assisting with the development of this web interface.
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