GetPartialEfSizes: GetPartialEfSizes

In TillBirkner/metadeconfoundR: Covariate-Sensitive Analysis of Cross-Sectional High-Dimensional Data

GetPartialEfSizes

Description

GetPartialEfSizes takes MetaDeconfound output and genarates partial effect sizes for all significant associations

Usage

GetPartialEfSizes(
  featureMat,
  metaMat,
  metaDeconfOutput,
  doRanks = NA,
  randomVar = NA,
  fixedVar = NA
)

Arguments

featureMat	a data frame with row(sample ID) and column(feature such as metabolite or microbial OTU ) names, listing features for all samples
metaMat	a data frame with row(sample ID) and column(meta data such as age,BMI and all possible confounders) names listing metadata for all samples. first column should be case status with case=1 and control=0. All binary variables need to be in 0/1 syntax!
metaDeconfOutput	long format output of the MetaDeconfound output created for the supplied featureMat and metaMat
doRanks	optional vector of metavariable names, that should be rank transformed when building linear models in the doconfounding step
randomVar	optional vector of metavariable names to be treated as random effect variables. These variables will not be tested for naive associations and will not be included as potential confounders, but will be added as random effects "+ (1|variable)" into any models being built. Any associations reducible to the supplied random effect(s) will be labeled as "NS". Note: Ps, Qs, Ds are computed independently and thereby not changed through inclusion of random effects.
fixedVar	optional vector of metavariable names to be treated as fixed effect variables. These variabels will not be tested for naive associations and will not be included as potential confounders, but will be added as fixed effects "+ variable" into any models being built. Any associations reducible to the supplied fixed effect(s) will be labeled as "NS". Note: Ps, Qs, Ds are computed independently and thereby not changed through inclusion of fixed effects.

Details

for more details and explanations please see the package vignette.

Value

long format data.frame similar to Metadeconfound() output

Examples

data(reduced_feature)
data(metaMatMetformin)


example_output <- MetaDeconfound(featureMat = reduced_feature,
                                  metaMat = metaMatMetformin,
                                  logLevel = "ERROR",
                                  returnLong = TRUE)
#
ex_out_partial <- GetPartialEfSizes(featureMat = reduced_feature,
                                      metaMat = metaMatMetformin,
                                      metaDeconfOutput = example_output)

TillBirkner/metadeconfoundR documentation built on Oct. 25, 2024, 11:12 a.m.