Performs a meta-analysis of TF-target edges across multiple studies using either a fixed-effect or DerSimonian-Laird random-effects model. Missing or non-finite effect sizes and standard errors are excluded from the corresponding study. A TF-target pair is only counted as contributing to a study when both its effect size and SE are valid.
maEdges(
edgesList,
method = c("random", "fixed"),
minStudies = 2L,
padjustMethod = "BH",
moderateVariance = TRUE,
s0 = NULL
)A data.frame containing:
tf: Transcription factor
target: Target gene
k: Number of studies contributing to the meta-analysis
log2FoldChange: Meta-analytic effect size
SE: Meta-analysis standard error
ciLow: Lower bound of the 95% confidence interval
ciHigh: Upper bound of the 95% confidence interval
zStatistic: Test statistic
pValue: Raw p-value
pAdj: Adjusted p-value
Q: Cochran's Q heterogeneity statistic
iSquared: I-squared heterogeneity (percentage)
tauSquared: DerSimonian-Laird between-study variance
A list of data.frames, one per study, typically produced by
testEdges. Each data.frame must contain the columns
tf, target, log2FoldChange and SE.
Meta-analysis model. Either "random" (DerSimonian-Laird
random-effects) or "fixed" (inverse-variance fixed-effect). Default
is "random".
Minimum number of studies with valid numeric information required for a TF-target pair to be included. Default 2.
Character specifying the p-value adjustment method for multiple
testing correction. See p.adjust for options. Default "BH"
(Benjamini-Hochberg FDR).
Logical indicating whether to apply SAM-style variance moderation to the meta-analysis SE. Default TRUE.
Optional variance-moderation fudge factor. If NULL and
moderateVariance = TRUE, the median of all valid meta-analysis SEs
is used.
Daniel Osorio <daniecos@uio.no>
runSCORPION, testEdges, circosEdges