ArticleDatabase : the journal of biological databases and curation2017
Duplicates, redundancies and inconsistencies in the primary nucleotide databases: a descriptive study.
Article in Database : the journal of biological databases and curation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
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- Integration of background knowledge for automatic detection of inconsistencies in gene ontology annotation.Bioinformatics (Oxford, England) · 2024Article
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- Propagation, detection and correction of errors using the sequence database network.Briefings in bioinformatics · 2022Review
- Exploring automatic inconsistency detection for literature-based gene ontology annotation.Bioinformatics (Oxford, England) · 2022Article
- msRepDB: a comprehensive repetitive sequence database of over 80 000 species.Nucleic acids research · 2022Article
- NanoRTax, a real-time pipeline for taxonomic and diversity analysis of nanopore 16S rRNA amplicon sequencing data.Computational and structural biotechnology journal · 2022Article
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- Building of an Internal Transcribed Spacer (ITS) Gene Dataset to Support the Italian Health Service in Mushroom Identification.Foods (Basel, Switzerland) · 2021Article
- Nanopore sequencing and its application to the study of microbial communities.Computational and structural biotechnology journal · 2021Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
GenBank, the EMBL European Nucleotide Archive and the DNA DataBank of Japan, known collectively as the International Nucleotide Sequence Database Collaboration or INSDC, are the three most significant nucleotide sequence databases. Their records are derived from laboratory work undertaken by different individuals, by different teams, with a range of technologies and assumptions and over a period of decades. As a consequence, they contain a great many duplicates, redundancies and inconsistencies, but neither the prevalence nor the characteristics of various types of duplicates have been rigorously assessed. Existing duplicate detection methods in bioinformatics only address specific duplicate types, with inconsistent assumptions; and the impact of duplicates in bioinformatics databases has not been carefully assessed, making it difficult to judge the value of such methods. Our goal is to assess the scale, kinds and impact of duplicates in bioinformatics databases, through a retrospective analysis of merged groups in INSDC databases. Our outcomes are threefold: (1) We analyse a benchmark dataset consisting of duplicates manually identified in INSDC-a dataset of 67 888 merged groups with 111 823 duplicate pairs across 21 organisms from INSDC databases - in terms of the prevalence, types and impacts of duplicates. (2) We categorize duplicates at both sequence and annotation level, with supporting quantitative statistics, showing that different organisms have different prevalence of distinct kinds of duplicate. (3) We show that the presence of duplicates has practical impact via a simple case study on duplicates, in terms of GC content and melting temperature. We demonstrate that duplicates not only introduce redundancy, but can lead to inconsistent results for certain tasks. Our findings lead to a better understanding of the problem of duplication in biological databases.Database URL: the merged records are available at https://cloudstor.aarnet.edu.au/plus/index.php/s/Xef2fvsebBEAv9w.
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