Description Usage Arguments Details Value Author(s) References Examples
View source: R/cross.correlate.R
Cross-correlate columns of the input matrices
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x |
matrix (samples x features if annotation matrix) |
y |
matrix (samples x features if cross-correlated with annotations) |
method |
association method ('pearson', 'spearman', or 'bicor' for continuous; categorical for discrete) |
p.adj.threshold |
q-value threshold to include features |
cth |
correlation threshold to include features |
order |
order the results |
n.signif |
mininum number of significant correlations for each element |
mode |
Specify output format ('table' or 'matrix') |
p.adj.method |
p-value multiple testing correction method. One of the methods in p.adjust function ('BH' and others; see help(p.adjust)). Default: 'fdr' |
verbose |
verbose |
filter.self.correlations |
Filter out correlations between identical items. |
As the method=categorical (discrete) association measure for nominal (no order for levels) variables we use Goodman and Kruskal tau based on r-bloggers.com/measuring-associations-between-non-numeric-variables/ The 'bicor' method is from the WGCNA package.
List with cor, pval, pval.adjusted
Contact: Leo Lahti microbiome-admin@googlegroups.com
See citation('microbiome')
1 2 3 4 | data(peerj32)
d1 <- peerj32$microbes[1:20, 1:10]
d2 <- peerj32$lipids[1:20,1:10]
cc <- cross.correlate(d1, d2)
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