lmFitPaired: A wrapper function for the function 'lmFit' of the R...

In iCheck: QC Pipeline and Data Analysis Tools for High-Dimensional Illumina mRNA Expression Data

Description

A wrapper function for the function 'lmFit' of the R Bioconductor package 'limma' for paired data.

Usage

lmFitPaired(
    esDiff, 
    formula = ~1, 
    pos.var.interest = 0,
    pvalAdjMethod = "fdr", 
    alpha = 0.05, 
    probeID.var="ProbeID", 
    gene.var = "Symbol", 
    chr.var = "Chromosome", 
    verbose = TRUE)

Arguments

esDiff	An LumiBatch object containing log2 difference between cases and controls. fData(esDiff) should contains information about probe ID, chromosome number and gene symbol.
formula	An object of class formula. The intercept measures the effect of treatment. Other covariates measure the effects of their interaction and treatment. The p-values for the intercept will be output. No left handside of ~ should be specified since the response variable will be the expression level.
pos.var.interest	integer. Indicates which covariate on the right-hand-side of ~ in formula is the covariate of the interest. By default, it is the intercept pos.var.interest=0.
pvalAdjMethod	One of p-value adjustment methods provided by the R function p.adjust in R package stats: “holm”, “hochberg”, “hommel”, “bonferroni”, “BH”, “BY”, “fdr”, “none”.
alpha	Significance level. A test is claimed to be significant if the adjusted p-value < alpha.
probeID.var	character string. Name of the variable indicating probe ID in feature data set.
gene.var	character string. Name of the variable indicating gene symbol in feature data set.
chr.var	character string. Name of the variable indicating chromosome number in feature data set.
verbose	logical. Determine if intermediate output need to be suppressed. By default verbose=TRUE, intermediate output will be printed.

Details

This is a wrapper function of R Bioconductor functions lmFit and eBayes for paired data to make it easier to input design and output list of significant results.

Value

A list with the following elements:

n.sig	Number of significant tests after p-value adjustment.
frame	A data frame containing test results sorted according to the ascending order of unadjusted p-values for the intercept. The data frame contains 7 columns: probeIDs, geneSymbols (gene symbols of the genes where the probes come from), chr (numbers of chromosomes where the probes locate), stats (moderated t-statistics for the intercept), pval (p-values of the tests for the intercept), p.adj (adjusted p-values), pos (row numbers of the probes in the expression data matrix).
statMat	A matrix containing test statistics for all covariates and for all probes. Rows are probes and columns are covariates. The rows are ordered according to the ascending order of unadjusted p-values for the intercept.
pvalMat	A matrix containing pvalues for all covariates and for all probes. Rows are probes and columns are covariates. The rows are ordered according to the ascending order of unadjusted p-values for the intercept.
pval.quantile	Quantiles (minimum, 25 for all covariates including intercept provided in the input argument formula.
frame.unsorted	A data frame containing test results. The data frame contains 7 columns: probeIDs, geneSymbols (gene symbols of the genes where the probes come from), chr (numbers of chromosomes where the probes locate), stats (moderated t-statistics for the intercept), pval (p-values of the tests for the intercept), p.adj (adjusted p-values), pos (row numbers of the probes in the expression data matrix).
statMat.unsorted	A matrix containing test statistics for all covariates and for all probes. Rows are probes and columns are covariates.
pvalMat.unsorted	A matrix containing pvalues for all covariates and for all probes. Rows are probes and columns are covariates.
memGenes	A numeric vector indicating the cluster membership of probes (unsorted). memGenes[i]=1 if the i-th probe is significant (adjusted pvalue < alpha) with positive moderated t-statistic; memGenes[i]=2 if the i-th probe is nonsignificant ; memGenes[i]=3 if the i-th probe is significant with negative moderated t-statistic;
memGenes2	A numeric vector indicating the cluster membership of probes (unsorted). memGenes2[i]=1 if the i-th probe is significant (adjusted pvalue < alpha). memGenes2[i]=0 if the i-th probe is nonsignificant.
mu1	Mean expression levels for arrays for probe cluster 1 (average taking across all probes with memGenes value equal to 1.
mu2	Mean expression levels for arrays for probe cluster 2 (average taking across all probes with memGenes value equal to 2.
mu3	Mean expression levels for arrays for probe cluster 3 (average taking across all probes with memGenes value equal to 3.
ebFit	object returned by R Bioconductor function eBayes.

Author(s)

Weiliang Qiu <[e-mail]>, Brandon Guo <[e-mail]>, Christopher Anderson <[e-mail]>, Barbara Klanderman <[e-mail]>, Vincent Carey <[e-mail]>, Benjamin Raby <[e-mail]>

Examples

    # generate simulated data set from conditional normal distribution
    set.seed(1234567)
    es.sim = genSimData.BayesNormal(nCpGs = 100, 
      nCases = 20, nControls = 20,
      mu.n = -2, mu.c = 2,
      d0 = 20, s02 = 0.64, s02.c = 1.5, testPara = "var",
      outlierFlag = FALSE, 
      eps = 1.0e-3, applier = lapply) 
    print(es.sim)

  # although the generated data is not from 
  # paired design, we use it to illusrate the
  # usage of the function lmFitPaired 


res.limma = lmFitPaired(
  es = es.sim, 
  formula = ~as.factor(memSubj), 
  pos.var.interest = 0, # the intercept is what we are interested
  pvalAdjMethod = "fdr", 
  alpha = 0.05, 
  probeID.var = "probe", 
  gene.var = "gene", 
  chr.var = "chr", 
  verbose = TRUE)

iCheck documentation built on Nov. 8, 2020, 11:09 p.m.