Detect the condition-specific as outliers in for the first step on the SpeCond procedure

Description

Perform the first detection step of the SpeCond procedure. Use the fitting of the gene expression value with a mixture of normal distribution results and a set of rules to detect the outliers. It returns the outliers detected as specifically expressed for each gene.

Usage

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getSpecificOutliersStep1(expressionMatrix, fit1 = NULL, 
param.detection = NULL, multitest.correction.method = "BY", 
prefix.file = NULL, print.hist.pv = FALSE)

Arguments

expressionMatrix

the gene expression matrix (genes * conditions)

fit1

the result of fitPrior containing the parameter of the mixture normal model of the expression data

param.detection

the parameter for the detection, a vector with the names ("per","md","mlk","rsd","pv") or the first row of the matrix obtained by getDefaultParameter or createParameterMatrix

multitest.correction.method

the multitest correction method. The default is "BY", for the possible values see p.adjust

prefix.file

a prefix added to the generated file. The default is NULL but has to be set. It is useful to change the prefix when you perform a new analysis. As you may want to compare the results with different parameters set.

print.hist.pv

to print in a pdf file the (non-adjusted) p-value histogram

Details

Frist essential method to obtain the matrix of expression value from your ExpressionSet to apply the SpeCond procedure step by step using the following function fitPrior, fitNoPriorwithExclusion, getSpecificOutliersStep1, getSpecificResult. The returned matrix will be the expressionMatrix argument of the above function

Value

A list of size the number of rows (genes) in the expressionMatrix. If the gene has outlier expression, the column number of this outlier is stored, NULL if not.

Author(s)

Florence Cavalli, florence@ebi.ac.uk

See Also

fitPrior, SpeCond, getSpecificResult

Examples

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library(SpeCond)
data(expressionSpeCondExample)
##Perform the SpeCond analysis step by step
param.detection=getDefaultParameter()
param.detection

fit1=fitPrior(expressionSpeCondExample, param.detection=param.detection)

specificOutlierStep1=getSpecificOutliersStep1(expressionSpeCondExample, 
 fit=fit1$fit1, param.detection, multitest.correction.method="BY",
 prefix.file="run1_Step1", print.hist.pv=FALSE)

##then use fitNoPriorWithExclusion() and getSpecificResult()