Title
AntiFam: a tool to help identify spurious ORFs in protein annotation.
Abstract
As the deluge of genomic DNA sequence grows the fraction of protein sequences that have been manually curated falls. In turn, as the number of laboratories with the ability to sequence genomes in a high-throughput manner grows, the informatics capability of those labs to accurately identify and annotate all genes within a genome may often be lacking. These issues have led to fears about transitive annotation errors making sequence databases less reliable. During the lifetime of the Pfam protein families database a number of protein families have been built, which were later identified as composed solely of spurious open reading frames (ORFs) either on the opposite strand or in a different, overlapping reading frame with respect to the true protein-coding or non-coding RNA gene. These families were deleted and are no longer available in Pfam. However, we realized that these may perform a useful function to identify new spurious ORFs. We have collected these families together in AntiFam along with additional custom-made families of spurious ORFs. This resource currently contains 23 families that identified 1310 spurious proteins in UniProtKB and a further 4119 spurious proteins in a collection of metagenomic sequences. UniProt has adopted AntiFam as a part of the UniProtKB quality control process and will investigate these spurious proteins for exclusion.
Year
DOI
Venue
2012
10.1093/database/bas003
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
Keywords
Field
DocType
computational biology,open reading frames,amino acid sequence,proteins,sequence alignment
Genome,Sequence alignment,Protein Families Database,UniProt,Computer science,Protein Annotation,ORFS,Bioinformatics,Molecular Sequence Annotation,Spurious relationship
Journal
Volume
ISSN
Citations 
2012
1758-0463
2
PageRank 
References 
Authors
1.15
5
6
Name
Order
Citations
PageRank
Ruth Y Eberhardt11472180.45
Daniel H. Haft21144230.24
Marco Punta31709194.79
Maria Jesus Martin42793365.41
Claire O'Donovan52584329.29
Alex Bateman654611054.58