From 0b7b32dc67712c5580af9a69722c029c13bc27a3 Mon Sep 17 00:00:00 2001 From: kkleinoros Date: Wed, 21 Dec 2016 10:18:43 -0500 Subject: [PATCH] S4 documentation --- DESCRIPTION | 3 +- R/SampleSet.R | 105 +++++++++++++++++++---------------- man/SampleSet-class.Rd | 8 ++- man/fromGenStudFiles.Rd | 12 ++-- man/fromRGChannelSet.Rd | 5 +- man/funtooNorm-package.Rd | 3 +- man/funtooNorm.Rd | 28 +++++++--- man/getGRanges.Rd | 16 ++++-- man/getNormBeta.Rd | 14 +++-- man/getNormM.Rd | 22 +++++--- man/getRawBeta.Rd | 14 +++-- man/getSnpM.Rd | 16 +++++- man/plotValidationGraph.Rd | 18 ++++-- man/show-SampleSet-method.Rd | 2 +- vignettes/funtooNorm.Rmd | 2 +- 15 files changed, 170 insertions(+), 98 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 7c78f03..012f8b5 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -4,7 +4,8 @@ Title: Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit Version: 0.99.7 Date: 2016-12-14 Author: Celia Greenwood ,Stepan Grinek - , Kathleen Klein + , Maxime Turgeon , + Kathleen Klein Maintainer: Kathleen Klein Description: Provides a function to normalize Illumina Infinium Human Methylation 450 BeadChip (Illumina 450K), correcting for tissue and/or cell diff --git a/R/SampleSet.R b/R/SampleSet.R index 5cfc7ce..af0beae 100644 --- a/R/SampleSet.R +++ b/R/SampleSet.R @@ -15,19 +15,20 @@ #' We then define then the 6 (2*3) labels: AIGrn BIGrn AIRed BIRed AII BII #' #' -#' @slot type character: is 'minfi' or 'GenomeStudio' +#' @slot type Character: is 'minfi' or 'GenomeStudio' #' @slot sampleNames character vector: #' contain the list of sample names in order used #' @slot sampleSize numeric: the number of samples #' @slot nPos numeric: the number of positions in the ILLUMINA chip -#' @slot annotation IlluminaMethylationAnnotation: the annotation object from +#' @slot annotation character: the annotation object from #' minfi package #' @slot cell_type factor: vector of the cell type for each sample as factors -#' @slot qntllist list: vector of ordered quantiles +#' @slot qntllist numeric: vector of ordered quantiles #' @slot quantiles list: list of 6 quantiles tables for the 6 signal types #' @slot ctl.covmat matrix: covariance matrix for the model fit #' @slot signal list: list of the values for all 6 probe types. #' @slot names list: list of probes for each type +#' @slot predmat list: list of the normalized values for all 6 probe types. #' #' @return a S4 object of class SampleSet #' @export @@ -60,12 +61,13 @@ setClass("SampleSet", representation(type = "character", #' @title Creates an object of class SampleSet from a RGChannelSet {minfi} #' -#' @description Creates a object of class SampleSet from the raw unprocessed data in RGChannelSet +#' @description Creates a object of class SampleSet from the raw unprocessed +#' data in RGChannelSet #' #' @param myRGChannelSet : RGChannelSet, from minfi package, should contain a #' cell_type vector in pData #' -#' @return a class 'SampleSet' object +#' @return An object of class 'SampleSet' #' @export #' #' @examples require(minfiData) @@ -195,13 +197,13 @@ fromRGChannelSet <- function(myRGChannelSet){ ################################################################################ #' Creates a S4 object of class 'SampleSet' from GenomeStudio files #' -#' @param controlProbeFile file of control probe data exported from GenomeStudio -#' @param signalFile file exported from GenomeStudio with the exact same samples -#' as control probe File -#' @param cell_type this vector should have names matching all the samples in -#' the files from genome studios, and at least 2 different cell types. +#' @param controlProbeFile The control probe file exported from GenomeStudio +#' @param signalFile The signals exported from GenomeStudio samples must be in +#' same order as the control probe File +#' @param cell_type A vector of cell types, names must match control probes and +#' signal files. #' -#' @return a SampleSet object +#' @return An object of class 'SampleSet'. #' @export #' fromGenStudFiles <- function(controlProbeFile,signalFile,cell_type){ @@ -307,7 +309,7 @@ fromGenStudFiles <- function(controlProbeFile,signalFile,cell_type){ #' Show Object SampleSet #' #' @description Display informations about the SampleSet object -#' @param x an object of class SampleSet +#' @param object an object of class SampleSet #' @param ... optional arguments passed to or from other methods. #' #' @export @@ -377,11 +379,11 @@ setMethod("getPositionNames", ) -#' Return a list +#' Build GRange object of methylation probes #' -#' @param object object of class SampleSet +#' @param object Object of class SampleSet. #' -#' @return a GRange object of all the methylated positions +#' @return A GRange object of the positions of each cpg. #' @export #' #' @examples require(minfiData) @@ -392,7 +394,7 @@ setMethod("getPositionNames", setGeneric(name="getGRanges", def=function(object) standardGeneric("getGRanges") ) - +#' @describeIn getGRanges Build GRange object of methylation probes setMethod("getGRanges", signature = "SampleSet", definition = function(object){ @@ -408,8 +410,7 @@ setMethod("getGRanges", ################################################################################ -#' Computes the beta value from the raw signal at each position for each -#' sample +#' Computes Beta value from raw signals #' #' @param object object of class SampleSet #' @param offset default is 100 as Illumina standard @@ -426,7 +427,7 @@ setMethod("getGRanges", setGeneric(name="getRawBeta", def=function(object, offset=100) standardGeneric("getRawBeta") ) - +#' @describeIn getRawBeta Computes Beta value from raw signals setMethod("getRawBeta", signature = "SampleSet", definition = function(object,offset){ @@ -440,8 +441,7 @@ setMethod("getRawBeta", ) ################################################################################ -#' Computes the beta value after normalization at each position for each -#' sample +#' Computes Beta values from normalized signals #' #' @param object of type SampleSet #' @param offset default is 100 as Illumina standard @@ -458,7 +458,7 @@ setMethod("getRawBeta", setGeneric(name="getNormBeta", def=function(object, offset=100) standardGeneric("getNormBeta") ) - +#' @describeIn getNormBeta Computes Beta values from normalized signals setMethod("getNormBeta", signature = "SampleSet", definition = function(object,offset){ @@ -475,14 +475,12 @@ setMethod("getNormBeta", ) ################################################################################ -#' Computes the M value after normalization at each position for each -#' sample +#' Computes M values,log2(Meth/Unmeth), from normalized signals #' -#' @param object of type SampleSet -#' @param offset default is 100 as Illumina standard +#' @param object An object of class SampleSet +#' @param offset Default is 100 as Illumina standard #' -#' @return a matrix containing M values, log2(Meth/Unmeth), after normalization at each position -#' for each samples. +#' @return a matrix containing M values, log2(Meth/Unmeth), after normalization #' @export #' #' @examples require(minfiData) @@ -493,7 +491,8 @@ setMethod("getNormBeta", setGeneric(name="getNormM", def=function(object) standardGeneric("getNormM") ) - +#' @describeIn getNormM Computes M values, log2(Meth/Unmeth), +#' from normalized signals setMethod("getNormM", signature = "SampleSet", definition = function(object){ @@ -508,11 +507,12 @@ setMethod("getNormM", ) ################################################################################ -#' Computes the M value after normalization for each SNP. +#' Computes M values after normalization of SNP data. #' #' @param object of class SampleSet #' -#' @return a matrix containing M values, log2(Meth/Unmeth), after normalization for each SNP +#' @return a matrix containing M values, log2(Meth/Unmeth), after normalization +#' for SNP data #' #' @export #' @@ -524,7 +524,8 @@ setMethod("getNormM", setGeneric(name="getSnpM", def=function(object) standardGeneric("getSnpM") ) - +#' @describeIn getSnpM Computes M values, log2(Meth/Unmeth), for normalized +#' SNP data setMethod("getSnpM", signature = "SampleSet", definition = function(object){ @@ -539,15 +540,20 @@ setMethod("getSnpM", ) ################################################################################ -#' This is the main normalization function which applies to autosomes and the X chromosome. +#' The funtooNorm normalization function +#' +#' \code{funtooNorm} +#' +#' This is a generic function which applies to autosomes and the X chromosome. #' Chromosome Y requires separate analysis as there are few probes on Y. #' We use a straightforward quantile normalization applied to males only. #' -#' @param object of class SampleSet -#' @param type.fits can be "PCR" or "PLS" (default "PCR") -#' @param ncmp number of components used in the analysis (default 4) -#' @param force when set to TRUE forces the normalization procedure to re-compute -#' @param sex boolean vector: if NULL Beta values from ChrY are used for classification. +#' @param object Object of class SampleSet +#' @param type.fits Choice between "PCR" or "PLS" (default="PCR") +#' @param ncmp Number of components included in the analysis (default=4) +#' @param force When set to TRUE forces the normalization procedure to re-compute +#' @param sex Boolean vector if male. if NULL Beta values from ChrY are used for +#' classification. #' #' @return a S4 object of class SampleSet containing the normalized signal #' @export @@ -558,9 +564,10 @@ setMethod("getSnpM", #' mySampleSet=funtooNorm(mySampleSet) #' setGeneric(name="funtooNorm", - def=function(object, type.fits="PCR",ncmp=4,force=FALSE,sex=NULL) standardGeneric("funtooNorm") + def=function(object, type.fits="PCR",ncmp=4,force=FALSE,sex=NULL) + standardGeneric("funtooNorm") ) - +#' @describeIn funtooNorm The funtooNorm normalization function setMethod("funtooNorm", signature = "SampleSet", definition = function(object,type.fits,ncmp,force,sex) @@ -570,9 +577,9 @@ setMethod("funtooNorm", ###### this part deal with chrY if(is.null(sex)){ mens=matrixStats::colMedians(calcBeta(object@signal$AchrY, - object@signal$BchrY))<0.6 - message("we found ",sum(mens)," men and ", - sum(!mens)," women in your data set base on Y probes only") + object@signal$BchrY))<0.6 + message("we found ",sum(mens)," men and ",sum(!mens), + " women in your data set base on Y probes only") }else{ mens=sex message("There is ",sum(mens)," men and ", @@ -607,8 +614,9 @@ setMethod("funtooNorm", ################################################################################ -#' Plot a series of graphs for each signal type, illustrating the effects -#' of the number of components included +#' @title plot of Validation Graph for determing number of components +#' @description Plots a series of graphs for each signal type, to determine +#' the number of components to include in the normalization procedure. #' #' @param object of class SampleSet #' @param type.fits can be "PCR" or "PLS" (default "PCR") @@ -623,9 +631,12 @@ setMethod("funtooNorm", #' plotValidationGraph(mySampleSet) #' setGeneric(name="plotValidationGraph", - def=function(object, type.fits="PCR",file=NULL) standardGeneric("plotValidationGraph") + def=function(object, type.fits="PCR",file=NULL) + standardGeneric("plotValidationGraph") ) - +#' @describeIn plotValidationGraph Plots a series of graphs for each +#' signal type, to determine the number of components to include +#' in the normalization procedure. setMethod("plotValidationGraph", signature = "SampleSet", definition = function(object,type.fits,file){ diff --git a/man/SampleSet-class.Rd b/man/SampleSet-class.Rd index 2046780..79c37cd 100644 --- a/man/SampleSet-class.Rd +++ b/man/SampleSet-class.Rd @@ -17,7 +17,7 @@ We then define then the 6 (2*3) labels: AIGrn BIGrn AIRed BIRed AII BII \section{Slots}{ \describe{ -\item{\code{type}}{character: is 'minfi' or 'GenomeStudio'} +\item{\code{type}}{Character: is 'minfi' or 'GenomeStudio'} \item{\code{sampleNames}}{character vector: contain the list of sample names in order used} @@ -26,12 +26,12 @@ contain the list of sample names in order used} \item{\code{nPos}}{numeric: the number of positions in the ILLUMINA chip} -\item{\code{annotation}}{IlluminaMethylationAnnotation: the annotation object from +\item{\code{annotation}}{character: the annotation object from minfi package} \item{\code{cell_type}}{factor: vector of the cell type for each sample as factors} -\item{\code{qntllist}}{list: vector of ordered quantiles} +\item{\code{qntllist}}{numeric: vector of ordered quantiles} \item{\code{quantiles}}{list: list of 6 quantiles tables for the 6 signal types} @@ -40,6 +40,8 @@ minfi package} \item{\code{signal}}{list: list of the values for all 6 probe types.} \item{\code{names}}{list: list of probes for each type} + +\item{\code{predmat}}{list: list of the normalized values for all 6 probe types.} }} \examples{ showClass("SampleSet") diff --git a/man/fromGenStudFiles.Rd b/man/fromGenStudFiles.Rd index fa24c8f..900aa55 100644 --- a/man/fromGenStudFiles.Rd +++ b/man/fromGenStudFiles.Rd @@ -7,16 +7,16 @@ fromGenStudFiles(controlProbeFile, signalFile, cell_type) } \arguments{ -\item{controlProbeFile}{file of control probe data exported from GenomeStudio} +\item{controlProbeFile}{The control probe file exported from GenomeStudio} -\item{signalFile}{file exported from GenomeStudio with the exact same samples -as control probe File} +\item{signalFile}{The signals exported from GenomeStudio samples must be in +same order as the control probe File} -\item{cell_type}{this vector should have names matching all the samples in -the files from genome studios, and at least 2 different cell types.} +\item{cell_type}{A vector of cell types, names must match control probes and +signal files.} } \value{ -a SampleSet object +An object of class 'SampleSet'. } \description{ Creates a S4 object of class 'SampleSet' from GenomeStudio files diff --git a/man/fromRGChannelSet.Rd b/man/fromRGChannelSet.Rd index e8b2ff7..1be8b78 100644 --- a/man/fromRGChannelSet.Rd +++ b/man/fromRGChannelSet.Rd @@ -11,10 +11,11 @@ fromRGChannelSet(myRGChannelSet) cell_type vector in pData} } \value{ -a class 'SampleSet' object +An object of class 'SampleSet' } \description{ -Creates a object of class SampleSet from the raw unprocessed data in RGChannelSet +Creates a object of class SampleSet from the raw unprocessed +data in RGChannelSet } \examples{ require(minfiData) diff --git a/man/funtooNorm-package.Rd b/man/funtooNorm-package.Rd index 0a1dc6b..3e834e1 100644 --- a/man/funtooNorm-package.Rd +++ b/man/funtooNorm-package.Rd @@ -17,7 +17,8 @@ Type: \tab Package\cr License: \tab GPL-3\cr } } -\author{Celia Greenwood, Raphael Poujol, Stepan Grinek, Kathleen Oros Klein} +\author{Celia Greenwood, Stepan Grinek, Raphael Poujol, Maxime Turgeon, +Kathleen Oros Klein} %\references{ %Literature or other references for background information diff --git a/man/funtooNorm.Rd b/man/funtooNorm.Rd index afcf129..8d885e8 100644 --- a/man/funtooNorm.Rd +++ b/man/funtooNorm.Rd @@ -1,33 +1,43 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/SampleSet.R +\docType{methods} \name{funtooNorm} \alias{funtooNorm} -\title{This is the main normalization function which applies to autosomes and the X chromosome. -Chromosome Y requires separate analysis as there are few probes on Y. -We use a straightforward quantile normalization applied to males only.} +\alias{funtooNorm,SampleSet-method} +\title{The funtooNorm normalization function} \usage{ funtooNorm(object, type.fits = "PCR", ncmp = 4, force = FALSE, sex = NULL) + +\S4method{funtooNorm}{SampleSet}(object, type.fits = "PCR", ncmp = 4, + force = FALSE, sex = NULL) } \arguments{ -\item{object}{of class SampleSet} +\item{object}{Object of class SampleSet} -\item{type.fits}{can be "PCR" or "PLS" (default "PCR")} +\item{type.fits}{Choice between "PCR" or "PLS" (default="PCR")} -\item{ncmp}{number of components used in the analysis (default 4)} +\item{ncmp}{Number of components included in the analysis (default=4)} -\item{force}{when set to TRUE forces the normalization procedure to re-compute} +\item{force}{When set to TRUE forces the normalization procedure to re-compute} -\item{sex}{boolean vector: if NULL Beta values from ChrY are used for classification.} +\item{sex}{Boolean vector if male. if NULL Beta values from ChrY are used for +classification.} } \value{ a S4 object of class SampleSet containing the normalized signal } \description{ -This is the main normalization function which applies to autosomes and the X chromosome. +\code{funtooNorm} + +This is a generic function which applies to autosomes and the X chromosome. Chromosome Y requires separate analysis as there are few probes on Y. We use a straightforward quantile normalization applied to males only. } +\section{Methods (by class)}{ +\itemize{ +\item \code{SampleSet}: The funtooNorm normalization function +}} \examples{ require(minfiData) pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3) diff --git a/man/getGRanges.Rd b/man/getGRanges.Rd index b8ec986..871df46 100644 --- a/man/getGRanges.Rd +++ b/man/getGRanges.Rd @@ -1,20 +1,28 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/SampleSet.R +\docType{methods} \name{getGRanges} \alias{getGRanges} -\title{Return a list} +\alias{getGRanges,SampleSet-method} +\title{Build GRange object of methylation probes} \usage{ getGRanges(object) + +\S4method{getGRanges}{SampleSet}(object) } \arguments{ -\item{object}{object of class SampleSet} +\item{object}{Object of class SampleSet.} } \value{ -a GRange object of all the methylated positions +A GRange object of the positions of each cpg. } \description{ -Return a list +Build GRange object of methylation probes } +\section{Methods (by class)}{ +\itemize{ +\item \code{SampleSet}: Build GRange object of methylation probes +}} \examples{ require(minfiData) pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3) diff --git a/man/getNormBeta.Rd b/man/getNormBeta.Rd index 7d1306e..21a242f 100644 --- a/man/getNormBeta.Rd +++ b/man/getNormBeta.Rd @@ -1,11 +1,14 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/SampleSet.R +\docType{methods} \name{getNormBeta} \alias{getNormBeta} -\title{Computes the beta value after normalization at each position for each -sample} +\alias{getNormBeta,SampleSet-method} +\title{Computes Beta values from normalized signals} \usage{ getNormBeta(object, offset = 100) + +\S4method{getNormBeta}{SampleSet}(object, offset = 100) } \arguments{ \item{object}{of type SampleSet} @@ -17,9 +20,12 @@ a matrix containing beta after normalization value for each CpG position and each samples } \description{ -Computes the beta value after normalization at each position for each -sample +Computes Beta values from normalized signals } +\section{Methods (by class)}{ +\itemize{ +\item \code{SampleSet}: Computes Beta values from normalized signals +}} \examples{ require(minfiData) pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3) diff --git a/man/getNormM.Rd b/man/getNormM.Rd index 4ff2f2e..e47c0d0 100644 --- a/man/getNormM.Rd +++ b/man/getNormM.Rd @@ -1,25 +1,31 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/SampleSet.R +\docType{methods} \name{getNormM} \alias{getNormM} -\title{Computes the M value after normalization at each position for each -sample} +\alias{getNormM,SampleSet-method} +\title{Computes M values,log2(Meth/Unmeth), from normalized signals} \usage{ getNormM(object) + +\S4method{getNormM}{SampleSet}(object) } \arguments{ -\item{object}{of type SampleSet} +\item{object}{An object of class SampleSet} -\item{offset}{default is 100 as Illumina standard} +\item{offset}{Default is 100 as Illumina standard} } \value{ -a matrix containing M values, log2(Meth/Unmeth), after normalization at each position -for each samples. +a matrix containing M values, log2(Meth/Unmeth), after normalization } \description{ -Computes the M value after normalization at each position for each -sample +Computes M values,log2(Meth/Unmeth), from normalized signals } +\section{Methods (by class)}{ +\itemize{ +\item \code{SampleSet}: Computes M values, log2(Meth/Unmeth), +from normalized signals +}} \examples{ require(minfiData) pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3) diff --git a/man/getRawBeta.Rd b/man/getRawBeta.Rd index b6caafb..da01e8f 100644 --- a/man/getRawBeta.Rd +++ b/man/getRawBeta.Rd @@ -1,11 +1,14 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/SampleSet.R +\docType{methods} \name{getRawBeta} \alias{getRawBeta} -\title{Computes the beta value from the raw signal at each position for each -sample} +\alias{getRawBeta,SampleSet-method} +\title{Computes Beta value from raw signals} \usage{ getRawBeta(object, offset = 100) + +\S4method{getRawBeta}{SampleSet}(object, offset = 100) } \arguments{ \item{object}{object of class SampleSet} @@ -17,9 +20,12 @@ a matrix containing the raw beta value for each position and each samples } \description{ -Computes the beta value from the raw signal at each position for each -sample +Computes Beta value from raw signals } +\section{Methods (by class)}{ +\itemize{ +\item \code{SampleSet}: Computes Beta value from raw signals +}} \examples{ require(minfiData) pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3) diff --git a/man/getSnpM.Rd b/man/getSnpM.Rd index 834f51a..3ab3d56 100644 --- a/man/getSnpM.Rd +++ b/man/getSnpM.Rd @@ -1,20 +1,30 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/SampleSet.R +\docType{methods} \name{getSnpM} \alias{getSnpM} -\title{Computes the M value after normalization for each SNP.} +\alias{getSnpM,SampleSet-method} +\title{Computes M values after normalization of SNP data.} \usage{ getSnpM(object) + +\S4method{getSnpM}{SampleSet}(object) } \arguments{ \item{object}{of class SampleSet} } \value{ -a matrix containing M values, log2(Meth/Unmeth), after normalization for each SNP +a matrix containing M values, log2(Meth/Unmeth), after normalization +for SNP data } \description{ -Computes the M value after normalization for each SNP. +Computes M values after normalization of SNP data. } +\section{Methods (by class)}{ +\itemize{ +\item \code{SampleSet}: Computes M values, log2(Meth/Unmeth), for normalized +SNP data +}} \examples{ require(minfiData) pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3) diff --git a/man/plotValidationGraph.Rd b/man/plotValidationGraph.Rd index 126f35e..38cf8f7 100644 --- a/man/plotValidationGraph.Rd +++ b/man/plotValidationGraph.Rd @@ -1,11 +1,15 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/SampleSet.R +\docType{methods} \name{plotValidationGraph} \alias{plotValidationGraph} -\title{Plot a series of graphs for each signal type, illustrating the effects - of the number of components included} +\alias{plotValidationGraph,SampleSet-method} +\title{plot of Validation Graph for determing number of components} \usage{ plotValidationGraph(object, type.fits = "PCR", file = NULL) + +\S4method{plotValidationGraph}{SampleSet}(object, type.fits = "PCR", + file = NULL) } \arguments{ \item{object}{of class SampleSet} @@ -16,9 +20,15 @@ plotValidationGraph(object, type.fits = "PCR", file = NULL) included} } \description{ -Plot a series of graphs for each signal type, illustrating the effects - of the number of components included +Plots a series of graphs for each signal type, to determine +the number of components to include in the normalization procedure. } +\section{Methods (by class)}{ +\itemize{ +\item \code{SampleSet}: Plots a series of graphs for each +signal type, to determine the number of components to include +in the normalization procedure. +}} \examples{ require(minfiData) pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3) diff --git a/man/show-SampleSet-method.Rd b/man/show-SampleSet-method.Rd index 45f3ac6..b11c928 100644 --- a/man/show-SampleSet-method.Rd +++ b/man/show-SampleSet-method.Rd @@ -8,7 +8,7 @@ \S4method{show}{SampleSet}(object) } \arguments{ -\item{x}{an object of class SampleSet} +\item{object}{an object of class SampleSet} \item{...}{optional arguments passed to or from other methods.} } diff --git a/vignettes/funtooNorm.Rmd b/vignettes/funtooNorm.Rmd index 38ec615..bc60754 100644 --- a/vignettes/funtooNorm.Rmd +++ b/vignettes/funtooNorm.Rmd @@ -1,7 +1,7 @@ --- title: "Normalizing Illumina Infinium Human Methylation 450k for multiple cell types with funtooNorm" author: "\\ - Celia Greenwood^1,2^, Stepan Grinek^1^, Raphael Poujol^1^, Kathleen Oros Klein^1^\\ + Celia Greenwood^1,2^, Stepan Grinek^1^, Raphael Poujol^1^, Maxime Turgeon^2^, Kathleen Oros Klein^1^\\ [1] Lady Davis Institute of Research, Montreal Quebec. [2] McGill University, Montreal Quebec." date: "`r Sys.Date()`"