calculateES: Calculation of Effects Sizes and their variance

In Juananvg/DExMA: Differential Expression Meta-Analysis

Calculation of Effects Sizes and their variance

Description

This function uses the Hedges'g estimator to calulate the different Effects size and their variances for each genes and for each dataset.

Usage

calculateES(objectMA, missAllow = 0.3)

Arguments

objectMA	A list of list. Each list contains two elements. The first element is the expression matrix (genes in rows and sample in columns) and the second element is a vector of zeros and ones that represents the state of the diffenrent samples of the expression matrix. 0 represents one group (controls) and 1 represents the other group (cases). The result of the CreateobjectMA can be used too.
missAllow	a number that indicates the maximun proportion of missing values allowed in a sample. If the sample has more proportion of missing values the sample will be eliminated. In the other case the missing values will be imputed using the K-NN algorithm.

Value

A list formed by three elements:

• First element (ES) is a dataframe were columns are each of the studies (datasets) and rows are the genes. Each element of the dataframe represents the Effect Size.

• Second element (Var) is a dataframe were columns are each of the studies (datasets) and rows are the genes. Each element of the dataframe represents the variance of the Effect size.

• Third element (logFC) is a dataframe were columns are each of the studies (datasets) and rows are the genes. Each element of the dataframe represents the log Fold Changes.

Author(s)

Juan Antonio Villatoro Garcia, [e-mail]

See Also

createObjectMA, metaAnalysisDE

Examples

data(DExMAExampleData)

resultsEffects <- calculateES(objectMA = maObject, missAllow = 0.3)
resultsEffects

Juananvg/DExMA documentation built on Dec. 5, 2023, 1:12 p.m.