Expression Atlas data in R

For differential expression 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.

Experiment page download button screenshot

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.

New R session screenshot

Load the object you downloaded into your R session, e.g.:

load( "/path/to/E-GEOD-38400-atlasExperimentSummary.Rdata" )

Load Atlas Rdata object screenshot

This has created an object called experimentSummary. This object is a SimpleList object. Each element is one of three Bioconductor objects:

How to use it

In order to use the object you will need to install and load the GenomicRanges package from Bioconductor.

If you have not already installed this package, do this by running the following two commands:

source( "http://bioconductor.org/biocLite.R" )

biocLite( "GenomicRanges" )

Now load the package into your R session:

library( GenomicRanges )

Load GenomicRanges screenshot

For more details about using using this package please see the documentation.

RNA-seq data

Data from an RNA-seq experiment is contained in a single SummarizedExperiment object in the SimpleList you have loaded.

The SummarizedExperiment object is stored under the name "rnaseq", so you can assign it to a new variable like this:

summarizedExperiment <- experimentSummary$rnaseq

SummarizedExperiment screenshot

The SummarizedExperiment object contains the following:

  • Matrix of raw counts (not normalized), in the assays slot, in a counts element.
  • SummarizedExperiment counts screenshot
  • Sample annotations, in the colData slot.
  • SummarizedExperiment coldata screenshot
  • Brief outline of methods, from QC of FASTQ files to production of raw counts, in the exptData slot.
  • SummarizedExperiment exptdata screenshot

For more information on how to use a SummarizedExperiment object, please see the documentation from Bioconductor.

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.

Multiple array design names screenshot

You can access each ExpressionSet via its array design accession, by typing e.g. expressionSet <- experimentSummary[[ "A-AFFY-18" ]]

ExpressionSet screenshot

Each ExpressionSet object contains the following:

  • Matrix of normalized intensity values, in the assayData, accessed via: exprs( expressionSet )
  • ExpressionSet normalized intensities screenshot
  • Sample annotations, in the phenoData, accessed via: pData( expressionSet )
  • ExpressionSet phenodata screenshot
  • Brief outline of normalization method applied, in the experimentData slot, accessed via: preproc( experimentData( expressionSet ) )
  • ExpressionSet preproc screenshot

For more information on how to use an ExpressionSet object, please see the documentation from Bioconductor.

Two-colour microarray data

Data from a two-colour microarray experiment is stored in one or more MAList objects. As for ExpressionSet objects, there is one MAList per array design used in the experiment. This means you can access each MAList object via its ArrayExpress array design accession.

Each MAList object contains the following:

  • Vector of probe names, in the genes element.
  • Matrix of log2(fold-change) values, in the M element.
  • Matrix of LOESS normalized average intensities, in the A element.

MAList screenshot

For more information on how to use an MAList object, please see the documentation from Bioconductor.