Reannotated

Reannotated is the term used to describe the act of annotating data again or updating annotations to reflect new information, corrections, or expanded evidence. It is commonly applied to datasets that carry interpreted or labeled information, such as biological sequences, genomes, or large-scale functional data, but can pertain to any domain that relies on annotation.

In genomics and bioinformatics, reannotation involves revising gene models, regulatory elements, and other functional features of a genome in light of new sequencing data, improved assemblies, transcriptomic evidence, or proteomic evidence. Reannotation may add previously undetected genes, adjust exon–intron structures, refine coding status, and update functional descriptions or domain annotations. It often combines automated computational pipelines with manual curation to ensure accuracy and consistency across releases.

The process aims to improve accuracy, interoperability, and usability of annotated resources. Reannotated datasets can alter downstream analyses, such as gene expression studies or comparative genomics, and therefore are typically published as formal releases with documentation of changes, evidence supporting updates, and versioned identifiers to maintain provenance.

Challenges include maintaining clear version control, documenting the rationale for changes, and achieving consensus within the user community. Reannotation efforts must balance sensitivity and specificity, avoid breaking existing analyses, and coordinate with standards and nomenclature guidelines. Notable examples occur in major genome projects, where resources such as Ensembl, GENCODE, and RefSeq periodically issue reannotation releases to reflect advancing knowledge.

See also annotation, genome annotation, functional annotation, and data curation.