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SummarizedExperiment and Ranged#

When working with lab datasets in R, you’ll often see SummarizedExperiment (SE) and RangedSummarizedExperiment (RSE) objects. These are standard Bioconductor containers for storing assay data together with metadata. They form the foundation for more advanced containers like MultiAssayExperiment (MAE).

1. SummarizedExperiment (SE)#

🔹 What it is

A table-like container with:

  • Rows = features (genes, proteins, probes)
  • Columns = samples (patients, cell lines)

  • Plus two metadata tables:

  • rowData: feature info (gene ID, annotation)

  • colData: sample info (patient, treatment, outcome)

🔹 Why it matters

Instead of managing separate expression and metadata files, SE bundles them together so analyses stay consistent.

library(SummarizedExperiment)

counts <- matrix(rpois(100, 10), ncol = 5)
se <- SummarizedExperiment(
  assays = list(counts = counts),
  rowData = DataFrame(Gene = paste0("Gene", 1:20)),
  colData = DataFrame(Sample = paste0("S", 1:5), Treatment = c("A","A","B","B","B"))
)

se
For detailed explanations and examples, refer to the Bioconductor documentation: SummarizedExperiment vignette*

2. RangedSummarizedExperiment (RSE)#

🔹 What it is

A specialized SE where each row corresponds to a genomic range (chromosome, start, end), stored as a GRanges object.

🔹 Why it matters

Many assays (RNA-seq, ChIP-seq, variant calls) produce data tied to coordinates. RSE makes it easy to query or subset by genomic location.

library(GenomicRanges)

rowRanges <- GRanges(seqnames = "chr1", ranges = IRanges(start = 1:20, width = 100))
rse <- SummarizedExperiment(
  assays = list(counts = matrix(rpois(100, 10), ncol = 5)),
  rowRanges = rowRanges,
  colData = DataFrame(Sample = paste0("S", 1:5))
)

rse

For detailed explanations and examples, refer to the Bioconductor documentation: VariantExperiment vignette (RSE use case)

3. How They Connect to MultiAssayExperiment (MAE)#

  • SE is the base object for assays.
  • RSE extends SE with genomic ranges.
  • MAE (see separate page) collects multiple SE/RSE objects together for multi-omics integration.
MultiAssayExperiment
|-- ExperimentList
|     |-- SummarizedExperiment (e.g., RNA-seq)
|     |-- RangedSummarizedExperiment (e.g., mutations)
|     |-- SummarizedExperiment (e.g., proteomics)
|-- colData (patient metadata)
|-- sampleMap (patient ↔ assay IDs)

MultiAssayExperiment page in this handbook

Quick Comparison#

Object Rows Columns Best for
SE Features (genes, proteins) Samples Expression + metadata
RSE Genomic ranges (chr/start/end) Samples Range-based assays
MAE Multiple SE/RSE objects Samples Multi-omics integration