metaAnalysisDE: Performing Meta-analysis

In Juananvg/DExMA: Differential Expression Meta-Analysis

Performing Meta-analysis

Description

It performs meta-analysis using seven different methods.

Usage

metaAnalysisDE(
    objectMA = NULL,
    effectS = NULL,
    pvalues = NULL,
    weight = NULL,
    typeMethod = c("FEM", "REM", "maxP", "minP", "Fisher", 
                    "Stouffer", "ACAT"),
    missAllow = 0.3,
    proportionData = 0.5
)

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.
effectS	A list of two elements. The first element is a dataframe with genes in rows and studies in columns. Each component of the dataframe is the effect of a gene in a study. The second element of the list is also a dataframe with the same structure, but in this case each component of the dataframe represent the variance of the effect of a gene in a study. The third element of the list is also a dataframe with the same structure, but in this case each component of the dataframe represent the log fold change of a gene in a study. This argument should be only used in the case that objectMA argument is null.
pvalues	A list of two elements. The first element is a dataframe with genes in rows and studies in columns. Each component of the dataframe is the p-value of a gene in a study. The second element of the list is also a dataframe with the same structure, but in this case each component of the dataframe represent the log fold change of a gene in a study. This argument should be only used in the case that objectMA argument is null.
weight	A vector of the weights of each dataset. This argument should only be included in case objectMA is null and you want to use "Stouffer" or "ACAT" method.
typeMethod	A character that indicates the method to be peformed. See "Details"for more information
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. In case the objectMA has been previously imputed, this element is not necessary.
proportionData	The minimum proportion of datasets in which a gene must be contained to be included. By default, the gene must be contained in at least half of the datasets. In case the objectMA has been previously imputed, this element is not necessary.

Details

The different meta-analysis methods that can be applied are:

1. Effects sizes methods:

   • "FEM": Fixed Effects model

   • "REM": Random Effects model

2. P-value combination mehods

   • "Fisher": Fisher's methods

   • "Stouffer": Stouffer's method

   • "maxP": maximum p-value method (Wilkinson's method)

   • "minP": minimum p-value method (Tippett's method)

   • "ACAT": Aggregated Cauchy Association Test method

Value

A dataframe with the meta-analysis results. Depending on the applied method, a different dataframe is obtained. For more information see the package vignette.

Author(s)

Juan Antonio Villatoro Garcia, [e-mail]

References

Daniel Toro-Domínguez, Juan Antonio Villatoro-García, Jordi Martorell-Marugán, Yolanda Román-Montoya, Marta E Alarcón-Riquelme, Pedro Carmona-Sáez, A survey of gene expression meta-analysis: methods and applications, Briefings in Bioinformatics, 2020;, bbaa019, https://doi.org/10.1093/bib/bbaa019

Michael Dewey (2020). metap: meta-analysis of significance values.

Liu, Y., Chen, S., Li, Z., Morrison, A. C., Boerwinkle, E., & Lin, X. (2019). ACAT: A Fast and Powerful p Value Combination Method for Rare-Variant Analysis in Sequencing Studies. The American Journal of Human Genetics, 104(3), 410-421. https://doi.org/10.1016/j.ajhg.2019.01.002

Examples

data(DExMAExampleData)
ResultsMA <- metaAnalysisDE(objectMA=maObject, typeMethod="REM",
                            missAllow=0.3, proportionData=0.5)
ResultsMA

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