Expression Atlas data in R
For microarray and RNA-seq experiments in Expression Atlas, you can download a file containing the expression data and meta-data that you can load into R. Click the R button on the top-right of any differential experiment page to download one.
How to load an Atlas experiment summary in R
Start an R session on your computer. For details on how to get and use R, please see the documentation on the R project website.
In order to use the object you will need to install a few packages from Bioconductor. These are:
If you have not already installed these packages, do this by running the following two commands:
source( "http://bioconductor.org/biocLite.R" )
biocLite( c( "S4Vectors", "IRanges", "GenomicRanges", "SummarizedExperiment" ) )
For more details about using using this package please refer to Bioconductor.
Load the Expression Atlas data
Load the object you downloaded into your R session, e.g.:
load( "/path/to/E-GEOD-38400-atlasExperimentSummary.Rdata" )
- RangedSummarizedExperiment (RNA-seq experiments)
- ExpressionSet (1-colour microarray experiments)
- MAList (2-colour microarray experiments)
How to use it
Data from an RNA-seq experiment is contained in a single RangedSummarizedExperiment object in the SimpleList you have loaded.
The RangedSummarizedExperiment object is stored under the name "rnaseq", so you can assign it to a new variable like this:
rSumExp <- experimentSummary$rnaseq
The RangedSummarizedExperiment object contains the following:
- Matrix of raw counts (not normalized), in the assays slot, in a counts element.
- Sample annotations, in the colData slot.
- Brief outline of methods, from QC of FASTQ files to production of raw counts, in the metadata slot.
One-colour microarray data
Data from a one-colour, or single-channel, microarray experiment is stored in potentially multiple ExpressionSet objects in the SimpleList summary you have loaded. There is one ExpressionSet per array design used in the experiment. The ExpressionSets are indexed by the ArrayExpress accession of the array design used.
You can access each ExpressionSet via its array design accession, by typing
expressionSet <- experimentSummary[[ "A-AFFY-18" ]]
Each ExpressionSet object contains the following:
- Matrix of normalized intensity values, in the
assayData, accessed via:
exprs( expressionSet )
- Sample annotations, in the phenoData, accessed via:
pData( expressionSet )
- Brief outline of normalization method applied, in the
experimentData slot, accessed via:
preproc( experimentData( expressionSet ) )