NormalizeMets (version 0.25)

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

Description

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

Usage

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

Arguments

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.

Value

The result is an object of class `results'. @seealso comp.2.cc.fdr.

References

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

Examples

# NOT RUN {
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),])

# }