03reading: Topic: Reading Microarray Data from Files

In limma: Linear Models for Microarray Data

Description

This help page gives an overview of LIMMA functions used to read data from files.

Reading Target Information

The function readTargets is designed to help with organizing information about which RNA sample is hybridized to each channel on each array and which files store information for each array.

Reading Intensity Data

The first step in a microarray data analysis is to read into R the intensity data for each array provided by an image analysis program. This is done using the function read.maimages.

read.maimages optionally constructs quality weights for each spot using quality functions listed in QualityWeights.

If the data is two-color, then read.maimages produces an RGList object. If the data is one-color (single channel) then an EListRaw object is produced. In either case, read.maimages stores only the information required from each image analysis output file. read.maimages uses utility functions removeExt, read.imagene and read.columns. There are also a series of utility functions which read the header information from image output files including readGPRHeader, readImaGeneHeader and readGenericHeader.

read.ilmn reads probe or gene summary profile files from Illumina BeadChips, and produces an ElistRaw object.

read.idat reads Illumina files in IDAT format, and produces an EListRaw object. detectionPValues can be used to add detection p-values.

The function as.MAList can be used to convert a marrayNorm object to an MAList object if the data was read and normalized using the marray and marrayNorm packages.

Reading the Gene List

Most image analysis software programs provide gene IDs as part of the intensity output files, for example GenePix, Imagene and the Stanford Microarray Database do this. In other cases the probe ID and annotation information may be in a separate file. The most common format for the probe annotation file is the GenePix Array List (GAL) file format. The function readGAL reads information from a GAL file and produces a data frame with standard column names.

The function getLayout extracts from the GAL-file data frame the print layout information for a spotted array. The functions gridr, gridc, spotr and spotc use the extracted layout to compute grid positions and spot positions within each grid for each spot. The function printorder calculates the printorder, plate number and plate row and column position for each spot given information about the printing process. The utility function getSpacing converts character strings specifying spacings of duplicate spots to numeric values.

The Australian Genome Research Facility in Australia often produces GAL files with composite probe IDs or names consisting of multiple strings separated by a delimiter. These can be separated into name and annotation information using strsplit2.

If each probe is printed more than once of the arrays in a regular pattern, then uniquegenelist will remove duplicate names from the gal-file or gene list.

Identifying Control Spots

The functions readSpotTypes and controlStatus assist with separating control spots from ordinary genes in the analysis and data exploration.

Manipulating Data Objects

cbind, rbind, merge allow different RGList or MAList objects to be combined. cbind combines data from different arrays assuming the layout of the arrays to be the same. merge can combine data even when the order of the probes on the arrays has changed. merge uses utility function makeUnique.

Author(s)

Gordon Smyth

See Also

01.Introduction, 02.Classes, 03.ReadingData, 04.Background, 05.Normalization, 06.LinearModels, 07.SingleChannel, 08.Tests, 09.Diagnostics, 10.GeneSetTests, 11.RNAseq

limma documentation built on Nov. 8, 2020, 8:28 p.m.