Corr: Computes correlation matrix for a metabolomics dataset or...
In NormalizeMets: Analysis of Metabolomics Data

Description Usage Arguments Value Author(s) References Examples

Computes correlation matrix for a metabolomics dataset or compares the correlation between two metabolomics datasets

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Corr(featuredata1 = NULL, featuredata2 = NULL, method = c("pearson",
  "kendall", "spearman"), padjmethod = c("BH", "holm", "hochberg", "hommel",
  "bonferroni", "BY", "fdr", "none"), saveoutput = FALSE, outputname = NULL)

`featuredata1`	A data frame in the featuredata format. This is a dataframe with metabolites in columns and samples in rows. Unique sample names should be provided as row names.
`featuredata2`	A data frame in the featuredata format. This is a dataframe with metabolites in columns and samples in rows. Unique sample names should be provided as row names.
`method`	Must be one of "pearson", "spearman" or "kendall"
`padjmethod`	p-value adjustment method. Must be one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr" or "none"
`saveoutput`	A logical indicating whether the results should be saved as a .csv file.
`outputname`	The name of the output file if the output has to be saved.

The result is an object of class ‘results’. @seealso comp.2.cc.fdr.

Alysha M De Livera, Gavriel Olshansky

Fukushima, A. Gene (2013) 518, 209-214

data("featuredata_roots")
featuredata_roots[featuredata_roots==0]<-NA
imp_data<-MissingValues(LogTransform(featuredata_roots)$featuredata)$featuredata
Corr( imp_data[c(1:17),], imp_data[c(18:37),])
Corr( imp_data[c(1:17),])