ABSTRACT
Genome annotation conceptually consists of inferring and assigning biological information to gene products. Over the years, numerous pipelines and computational tools have been developed aiming to automate this task and assist researchers in gaining knowledge about target genes of study. However, even with these technological advances, manual annotation or manual curation is necessary, where the information attributed to the gene products is verified and enriched. Despite being called the gold standard process for depositing data in a biological database, the task of manual curation requires significant time and effort from researchers who sometimes have to parse through numerous products in various public databases. To assist with this problem, we present CODON, a tool for manual curation of genomic data, capable of performing the prediction and annotation process. This software makes use of a finite state machine in the prediction process and automatically annotates products based on information obtained from the Uniprot database. CODON is equipped with a simple and intuitive graphic interface that assists on manual curation, enabling the user to decide about the analysis based on information as to identity, length of the alignment, and name of the organism in which the product obtained a match. Further, visual analysis of all matches found in the database is possible, impacting significantly in the curation task considering that the user has at his disposal all the information available for a given product. An analysis performed on eleven organisms was used to test the efficiency of this tool by comparing the results of prediction and annotation through CODON to ones from the NCBI and RAST platforms.
Subject(s)
Bacteria/genetics , Genomics/methods , Molecular Sequence Annotation/methods , Software , Databases, Genetic , User-Computer InterfaceABSTRACT
The availability of biological information in public databases has increased exponentially. To ensure the accuracy of this information, researchers have adopted several methods and refinements to avoid the dissemination of incorrect information; for example, several automated tools are available for annotation processes. However, manual curation ensures and enriches biological information. Additionally, the genomic finishing process is complex, resulting in increased deposition of drafts genomes. This introduces bias in other omics analyses because incomplete genomic content is used. This is also observed for complete genomes. For example, genomes generated by reference assembly may not include new products in the new sequence or errors or bias can occur during the assembly process. Thus, we developed ImproveAssembly, a tool capable of identifying new products missing from genomic sequences, which can be used for complete and draft genomes. The identified products can improve the annotation of complete genomes and drafts while significantly reducing the bias when the information is used in other omics analyses.
