MAP.Matches: Wrapper function for MAP-Matches method

In MAMA: Meta-Analysis of MicroArray

Description

This is a wrapper function for MAP-Matches method.

Usage

MAP.Matches(data, varname, t.cutoff = "98.00%", multiple = TRUE, perm = c("both", "columns", "labels")[1], nperm = 1000, test = c("t", "t.equalvar")[1], sig.col, sig.cutoff = 0.05)

Arguments

data	Object of class MetaArray
varname	Character String - name of one column in clinical data matrices to be used as class labels
t.cutoff	Character String - quantile of T statistics to be selected, e.g. "95.00%" selects the top 5 percent of absolute values
multiple	Logical - when TRUE only paterrns with multiple '1' are used
perm	Character String - if "labels" only class labels are permuted for statistical analysis (empirical significance), if "columns" only genes in each dataset are selected randomly, if "both" both class labels and genes are permuted and two p-values returned
nperm	Numeric - number of permutations
test	Character String - if "t" then unequal variance t-test is used, if "t.equalvar" equal variance t-test is used
sig.col	Character String - which p-value is used for selection of significant patterns. Possible values are: "p.col.strong", "p.col.weak", "p.lab.strong", "p.lab.weak" , "col" refers to column permutations, "lab" to class labels, "weak" to soft match and "strong" to strong match
sig.cutoff	Numeric - p-value for selection of sigificant patterns

Value

Object of class MAP.Matches.res containing

tests	Data.frame of test statistics
bin.matrix	Binary matrix from tests, 1 means the test statistics was higer than threshold
sumarization	Sumarization of bin.matrix: number of selected genes in each dataset, genes with at least one 1 in pattern, probability of observing strong or soft match in the data
MAP	Data frame describing observed patterns: number of strong n.strong and soft n.soft matches and number of genes involved n.sig
stat.analysis	Results of statistical analysis
genes	List of genes observed with each pattern
all.genes	Names of the all genes in the analysis

Author(s)

Ivana Ihnatova

References

Yang, X., Bentink, S. and Spang, R. 2005, Detecting Common Gene Expression Patterns in Multiple Cancer Outcome Entities, Biomedical Microdevices, Vol.7:3, pp. 247-251

Examples

data(ColonData)
MAP.Matches(ColonData, "MSI", nperm = 100, sig.col="p.lab.strong")

MAMA documentation built on Jan. 15, 2017, 3:05 p.m.