Gene expression is the process by which the information in a gene is used to make a functional product, and reporting standards such as MIAME and MINSEQE define the minimum information needed to make expression experiments reproducible. Measuring expression tells researchers which genes are active and to what degree, and sharing that data usefully depends on describing the experiment completely.
This article explains gene expression at a high level and focuses on the data-reporting standards and repositories that make expression studies findable, interpretable and reusable.
What gene expression measures
Gene expression experiments quantify the activity of genes across a sample, often comparing conditions to see which genes are more or less active. Two broad measurement approaches dominate: microarrays, which use predefined probes, and high-throughput sequencing, which reads transcripts directly. Each approach generates large datasets whose interpretation depends on rich, standardised metadata — the kind of structured description catalogued in the CASRAI dictionary.
MIAME and MINSEQE: minimum information standards
To make expression data reproducible, the FGED Society developed minimum-information standards. MIAME (Minimum Information About a Microarray Experiment) sets out what must be reported for microarray studies, while MINSEQE (Minimum Information about a high-throughput SEQuencing Experiment) does the equivalent for sequencing-based experiments.
| Standard | Applies to | Purpose |
|---|---|---|
| MIAME | Microarray experiments | Define minimum information to interpret and reproduce results |
| MINSEQE | High-throughput sequencing experiments | Define minimum information for sequencing-based expression studies |
Both standards share a principle: a reader should be given enough information about the experimental design, samples, protocols and processed data to understand and, in principle, reproduce the study. This minimum-information approach is the same philosophy applied to method reporting in our guide to the MIQE qPCR guidelines.
What minimum information typically covers
Although the two standards target different technologies, the categories of required information are similar in spirit: a description of the experimental design and the relationships between samples; details of each sample and its treatment; the protocols used for measurement; and the raw and processed data along with the steps used to derive one from the other. Capturing these elements consistently is what allows independent reanalysis.
Public repositories: GEO and ArrayExpress
Standardised reporting works hand in hand with public repositories. GEO (Gene Expression Omnibus) and ArrayExpress are established archives that accept gene-expression datasets together with their descriptive metadata, assigning stable accession identifiers so the data can be cited and retrieved.
Depositing data in such repositories, described to the relevant minimum-information standard, supports the wider goals of our reproducibility coverage and aligns expression data with the FAIR principles discussed in our guide to genomic data-sharing standards. Persistent accessions also tie datasets back to their studies, as set out in our note on persistent identifiers in 2026. For documentation practice, see our guidance for authors.
Frequently asked questions
What is gene expression?
Gene expression is the process by which the information in a gene is used to make a functional product. Expression experiments measure which genes are active in a sample and to what degree, often by comparing conditions.
What is the difference between MIAME and MINSEQE?
MIAME defines the minimum information needed to report microarray experiments, while MINSEQE defines the equivalent minimum information for high-throughput sequencing experiments. Both aim to make expression studies interpretable and reproducible.
Where is gene-expression data shared?
Public repositories such as GEO (Gene Expression Omnibus) and ArrayExpress accept expression datasets with their descriptive metadata and assign stable accession identifiers so the data can be cited and retrieved.
Why do minimum-information standards matter?
They ensure that the design, samples, protocols and data of an experiment are described completely enough for independent researchers to interpret and, in principle, reproduce the study, reducing the risk of irreproducible results.
