metaAndPlot: Perform GLMM or inverse variance meta-analysis

In hui-sheen/MetaGSCA: Meta-analysis of Gene Set differential Co-expression Analysis

Perform GLMM or inverse variance meta-analysis

Description

Perform GLMM or inverse variance meta-analysis on original and bootstrap analysis results

Usage

metaAndPlot(
  lst,
  name.geneset,
  nperm = 500,
  nboot = 200,
  method = c("GLMM", "Inverse")[1],
  effect = c("random", "fixed")[1]
)

Arguments

lst	list of GSAR_boot() results for multiple datasets regarding one gene set
name.geneset	name of the concerned single gene set
nperm	times of sample indix permutation, necessitated by GSNCA
nboot	number of bootstrap times
method	method for meta analysis, either GLMM or Inverse (inverse)
effect	choice of effects model, either fixed or random

Details

1.GLMM may reject to apply if all individual datasets have identical proportion, so there is always special treatment on GLMM track considering this marginal condition. For bootstrap sample meta-analysis, used tryCatch() to ignore occasional marginal situation on individual bootstrap time. 2. Forest plot is generated in a PDF file. 3. method designates GLMM or Inverse. If inappropriate, change method to method.choice throughout. 4. Use single generic term to designate either fixed or random series.

Value

metaprop function result object together with p-values for multiple bootstrap meta-analyses.

hui-sheen/MetaGSCA documentation built on April 9, 2022, 7:24 p.m.