rankProbes | R Documentation |
Apply a linear model to Illumina's 450k or EPIC methylation data to get the t-value of each CpG probe
rankProbes(methData, pheno = NULL, paired = FALSE, explanatory = 1,
covariates = c(), pairColumn = c(), caseGroup = 1, refGroup = 2,
continuous = NULL, typeInput = "beta", typeAnalysis = "M")
methData |
A data frame or a matrix containing Illumina's CpG probes in rows and samples in columns. A SummarizedExperiment object can be used too |
pheno |
A data frame or a matrix containing samples in rows and covariates in columns. If NULL (default), pheno is extracted from the SummarizedExperiment object |
paired |
Perform a paired t-test (default = FALSE) |
explanatory |
The column name or position from pheno used to perform the comparison between groups (default = first column) |
covariates |
A list or character vector with column names from pheno used as data covariates in the linear model |
pairColumn |
Only for paired analysis. The column name or position from pheno used to connect the paired samples (default = NULL) |
caseGroup |
The group name or position from explanatory variable used as cases to perform the comparison (default = first group) |
refGroup |
The group name or position from explanatory variable used as reference to perform the comparison (default = second group) |
continuous |
A list or character vector with columns names from pheno which should be treated as continuous variables (default = none) |
typeInput |
Type of input methylation data. "beta" for Beta-values and "M" for M-values |
typeAnalysis |
"M" to use M-values to rank the CpG probes (default). "beta" to use Beta-values instead |
A named vector containing the t-values from the linear model for each CpG probe
Jordi Martorell Marugán, jordi.martorell@genyo.es
Smyth, G. K. (2005). Limma: linear models for microarray data. Bioinformatics and Computational Biology Solutions using R and Bioconductor, 397-420.
mCSEATest
data(mcseadata)
myRank <- rankProbes(betaTest, phenoTest, refGroup = "Control")
head(myRank)
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