Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system

• Published in: BMC genomics Vol. 17; no. 292; p. 307
• Main Authors: Chen, I-Min A, Markowitz, Victor M, Palaniappan, Krishna, Szeto, Ernest, Chu, Ken, Huang, Jinghua, Ratner, Anna, Pillay, Manoj, Hadjithomas, Michalis, Huntemann, Marcel, Mikhailova, Natalia, Ovchinnikova, Galina, Ivanova, Natalia N, Kyrpides, Nikos C
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 26.04.2016; BioMed Central; Springer
• Subjects: 60 APPLIED LIFE SCIENCES; Annotations; Authorship; Case studies; Citizen participation; Collaboration; Computational Biology - methods; Cooperative Behavior; Data Accuracy; Data warehouses; Datasets; Functional curation; Funding; Gene annotation; Genome, Microbial; Genomes; Genomics; Genomics - methods; IMG; Information Dissemination; Internet; Linux; Manual curation; MATHEMATICS AND COMPUTING; Metagenomics; Microbial genetics; Microbial genomics; Molecular Sequence Annotation - methods; Open access; Proteins; Scientists; Software; Usability; User interface; User-Computer Interface; United States; Metagenomics; IMG; Microbial genomics; Functional curation; Manual curation; Gene annotation
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-016-2629-y

The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existing IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.