filterGenes {MetaIntegrator}

Filter out significant genes from meta-analysis results

Description

After the Meta-Analysis results have been written to the metaObject, the results can be examined using different gene filtering criteria. This function will use the given filterParameter to select genes that fulfill the filter conditions. The function returns a modified version of the metaObject with results stored in metaObject$filterResults

Usage

filterGenes(metaObject, isLeaveOneOut = TRUE, effectSizeThresh = 0,
  FDRThresh = 0.05, numberStudiesThresh = 1,
  heterogeneityPvalThresh = 0)

Arguments

metaObject

a Meta object which must have the $originalData, $metaAnalysis populated

isLeaveOneOut

Do leave-one-out analysis on discovery datasets (default: TRUE). Needs at least 2 datasets for discovery.

effectSizeThresh

a gene is selected, if the absolute value of its effect size is above this threshold (default: 0)

FDRThresh

FDR cutoff: a gene is selected, if it has a p-value less than or equal to the FDR cutoff (default: 0.05)

numberStudiesThresh

number of studies in which a selected gene has to be significantly up/down regulated (default: 1)

heterogeneityPvalThresh

heterogeneity p-value cutoff (filter is off by default: heterogeneityPvalThresh = 0). Genes with significant heterogeneity and, thus a significant (low) heterogeneity p-value, can be filtered out by using e.g.: heterogeneityPvalThresh = 0.05 (removes all genes with heterogeneity p-value < 0.05)

Value

A modified version of the input metaObject with an additional filterObject stored within metaObject$filterResults

Note

Use checkDataObject(metaObject, "Meta", "Pre-Filter") to make sure your metaObject has the right format for filtering after running the meta-analysis with runMetaAnalysis().

Author(s)

Francesco Vallania

See Also

checkDataObject

Examples

	# filter genes with default settings 
	#(false discovery rate cutoff of 5 percent and WITH leave-one-out analysis)
	testMetaObject <- filterGenes(tinyMetaObject)
	summarizeFilterResults(testMetaObject, getMostRecentFilter(testMetaObject))
	
	# filter genes with false discovery rate of 1 percent and WITHOUT leave-one-out analysis  
	testMetaObject <- filterGenes(testMetaObject, FDRThresh = 0.01, isLeaveOneOut = FALSE)
	summarizeFilterResults(testMetaObject, getMostRecentFilter(testMetaObject))