In markdunning/beadarray-devel: Quality assessment and low-level analysis for Illumina BeadArray data

New beadarray functionality

A demonstration of the proposed new functionality for beadarray

library(beadarray)
library(GEOquery)
library(limma)
library(GenomicRanges)

A proposal is to faciliate the analyis of publicly-available data. We download the following example

url <- "ftp://ftp.ncbi.nih.gov/pub/geo/DATA/SeriesMatrix/GSE33126/"
filenm <- "GSE33126_series_matrix.txt.gz"
if(!file.exists("GSE33126_series_matrix.txt.gz")) download.file(paste(url, filenm, sep=""), destfile=filenm)
gse <- getGEO(filename=filenm)
head(exprs(gse))

We can convert into a beadarray object

#summaryData <- new("ExpressionSetIllumina", gse)
summaryData <- ExpressionSetIlluminaFromGEO(gse)
summaryData
head(fData(summaryData))

Detection scores could be added by using the no match probes as negative controls. Possibly we could assignment of status when the object is created?

fData(summaryData)$Status <- ifelse(fData(summaryData)$PROBEQUALITY=="No match","negative","regular" )

Detection(summaryData) <- calculateDetection(summaryData, status=fData(summaryData)$Status)

Likewise for normalisation

summaryData.norm <- normaliseIllumina(summaryData,method="neqc", status=fData(summaryData)$Status)
boxplot(summaryData.norm)

The user has to be able to select a column to use as Sample Groups

pData(summaryData)[1:3,]

SampleGroup(summaryData.norm) <- as.character(pData(summaryData)$source_name_ch1)

summaryData.norm <- simpleDE(summaryData.norm)

lapply(summaryData.norm@deResults, head)

beadarray:::volcanoplot(summaryData.norm)

A useful for function for picking the 'best' probe for each gene based on IQR (by default)

collapse
geneData <- beadarray:::collapse(summaryData)
geneData

A function that will get genomic locations for each probe and create a RangedData object

rng <- toRangedData(summaryData.norm)

markdunning/beadarray-devel documentation built on May 21, 2019, noon