heterogeneityTest: Checking the heterogeneity of the different studies

In Juananvg/DExMA: Differential Expression Meta-Analysis

Checking the heterogeneity of the different studies

Description

Shows a QQ-plot of the Cochran's test and the quantiles of I^2 statistic values to mesuare heterogeneity

Usage

heterogeneityTest(objectMA, probs = c(0, 0.25, 0.5, 0.75))

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 different 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.
probs	Numeric vector of probabilities with values between 0 and 1. It indicates the I^2 quantiles that will be returned

Details

If in the QQ-plot of the Cochran’s test most of the values are close to the central line (most of the Cochran’s test values are close to the expected distribution), it can be said that there is homogeneity. In the case that these values deviate greatly from the expected distribution, it must be assumed that there is heterogeneity. I^2 measures the percentage of variation across studies due to heterogeneity. To assume homogeneity in the gene expression meta-analysis, almost all I^2 values (quantiles) must be 0 or at least less than 0.25.

Value

Quantiles of the I^2 values

Author(s)

Juan Antonio Villatoro Garcia, [e-mail]

References

Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21:1539–58.

Higgins JPT, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ 2003;327:557–60.

See Also

createObjectMA

Examples

data(DExMAExampleData)

heterogeneityTest(maObject)

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