ds.lmFeature: Linear regression analysis of pooled data for each CpG site...

In isglobal-brge/dsOmicsClient: DataSHIELD client site Omics association functions.

Linear regression analysis of pooled data for each CpG site in study

Description

Performing a linear regression analysis on pooled data from multiple studies for every feature

Usage

ds.lmFeature(
  features = NULL,
  model,
  Set,
  type.p.adj = "fdr",
  cellCountsAdjust = FALSE,
  mc.cores = 1,
  datasources = NULL
)

Arguments

features	an optional parameter input as a vector of integer values which indicates the indices of specific features (e.g. genes, CpGs, ...) that should be analysed. If missing all features are analysed
model	formula indicating the condition (left side) and other covariates to be adjusted for (i.e. condition ~ covar1 + ... + covar2). The fitted model is: feature ~ condition + covar1 + ... + covarN
Set	name of the DataSHIELD object to which the ExpresionSet or RangedSummarizedExperiment has been assigned
type.p.adj	multiple comparison correction method. Default 'fdr'
cellCountsAdjust	logical value which indicates whether models should be adjusted for cell counts that are estimated using 'meffil.estimate.cell.counts.from.betas' function from meffil package.
mc.cores	optional parameter that allows the user to specify the number of CPU cores to use during parallel processing. Argument can only be > 1 when the function is run on a linux machine models should be adjusted for the estimated cell counts by including the variables in the models. NOTE: This assumes that the Opal pheno tables for every study include the necessary estimated cell count data originally computed when running the createOpalFiles function ##' @param datasources ....

Details

The function fits a generalized linear model of a ExpressionSet for each feature (gene, CpG site, ...) in the data sets considered, using user specified condition and covariates Outputs a matrix containing a beta value, standard error and p-value for each feature

isglobal-brge/dsOmicsClient documentation built on March 20, 2023, 3:52 p.m.