# Bioconductor Multiassayexperiment

> Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of st

- Skill: `biomate-ai/bioconductor-multiassayexperiment` (Agent Skill)
- Install (CLI): `npx skillmds@latest add biomate-ai/bioconductor-multiassayexperiment`
- Raw SKILL.md: https://api.skillmd.com/api/skills/biomate-ai/bioconductor-multiassayexperiment/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: biomate-ai (https://skillmd.com/u/biomate-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/biomate-ai/bioconductor-multiassayexperiment

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# MultiAssayExperiment

## Dependencies & Environment

> Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

- **Version:** 1.38.0 · **Bioconductor:** 3.23 · **R:** ≥ 4.6
- **Depends:** SummarizedExperiment
- **Imports:** Biobase, BiocBaseUtils, BiocGenerics, DelayedArray, GenomicRanges, IRanges, MatrixGenerics, S4Vectors, tidyr
- **Install:** `BiocManager::install("MultiAssayExperiment")`

## When to Use
- Integrating multi-omics experiments (e.g., DNA mutations, RNA abundance) measured on the same biological specimens into a single object.
- Managing complex experimental designs where a single patient maps to multiple assays, missing assays, or technical replicates using a `sampleMap`.
- Subsetting multiple experimental assays simultaneously by patient IDs, genomic ranges, or column metadata using `[`, `intersectColumns`, or `intersectRows`.
- Reshaping multi-assay data into long or wide formats for downstream analysis using `longFormat` or `wideFormat`.

## When NOT to Use
- For sets of assays with the exact same information across all rows (e.g., identical genes or genomic ranges), use `SummarizedExperiment` instead.

## Data Requirements
- **experiments**: A named `list` or `ExperimentList` containing assay datasets (e.g., `matrix`, `SummarizedExperiment`, `RangedSummarizedExperiment`, `RaggedExperiment`).
- **colData**: A `DataFrame` containing primary patient/specimen metadata, where rownames are patient identifiers.
- **sampleMap**: A three-column `DataFrame` (`assay`, `primary`, `colname`) that unambiguously maps experimental observations to rows in `colData`.

## Key Parameters
- **experiments**: A named list of experimental data objects provided to the `MultiAssayExperiment` constructor.
- **colData**: A `DataFrame` of primary metadata describing the biological units (e.g., patients).
- **sampleMap**: A `DataFrame` relating the primary data to the experimental assays.
- **metadata**: A list of study-wide metadata (e.g., citation information) attached to the object.

## Best Practices
- Run the `prepMultiAssay` helper function before constructing the object to diagnose and resolve inconsistent names between the `ExperimentList`, `colData`, and `sampleMap`.
- Use the `listToMap` convenience function to easily convert a list of platform-specific data frames into a valid `sampleMap`.
- Store study-wide metadata, such as citation information, using the `metadata` slot at the `MultiAssayExperiment` level.
- Ensure all elements in the `ExperimentList` are named; unnamed elements will prompt an error during construction.

## Common Pitfalls
- **Unnamed ExperimentList**: Passing an unnamed list of experiments to the constructor or `prepMultiAssay` causes an error. *Fix*: Assign names to the list elements (e.g., `names(objlist) <- c("Affy", "Methyl")`) before construction.
- **Dropped Samples**: Assay samples (colnames) that cannot be mapped to a corresponding row in `colData` via the `sampleMap` are silently dropped. *Fix*: Check the `$drops` element returned by `prepMultiAssay` to identify and fix unmatched identifiers.
- **Mismatched sampleMap Columns**: Providing a `sampleMap` without the exact column names `assay`, `primary`, and `colname`. *Fix*: Ensure the `sampleMap` strictly adheres to this three-column naming convention.

## Alternatives
- **SummarizedExperiment**: Recommended for single-assay datasets or multiple assays that share the exact same row features (e.g., identical genomic ranges).

## Citations
- Ramos, M., et al. (2017). Software for the Integration of Multi-Omics Experiments in Bioconductor. Cancer Research.

## References
- Homepage: https://bioconductor.org/packages/MultiAssayExperiment
- Vignette: https://bioconductor.org/packages/release/bioc/vignettes/MultiAssayExperiment/inst/doc/MultiAssayExperiment.html

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## Run this on BioMate

This skill is the **knowledge layer** — when, why, and how to use `multiassayexperiment`. To **run this analysis on your own data** with managed compute, automated QC, and reproducible outputs, use **[BioMate](https://www.biomate.ai?ref=kb&pkg=multiassayexperiment)** — free to start.

▶ **[Open `multiassayexperiment` on BioMate →](https://www.biomate.ai?ref=kb&pkg=multiassayexperiment)**