An effective biomedical data migration tool from resource description framework to JSON

Jointly Integrating VCF-Based Variants and OWL-Based Biomedical Ontologies in MongoDB

The development of the next-generation sequencing (NGS) technologies has led to massive amounts of VCF (Variant Call Format) files, which have been the standard formats developed with 1000 Genomes Project. At the same time, with the widespread use of biomedical ontologies in the biomedical community, more and more applications have accepted the Web Ontology Language (OWL) as the dominant data format for the specifications of biomedical ontology descriptions, leading to the rapid growth of OWL-based biomedical ontology scale. In this paper, we seek to explore an effective method for the management of VCF-based genetic variants and OWL-based biological ontologies using the MongoDB database. Considering many current applications (such as the short genetic variations database dbSNP, etc.) are transitioning to the new design by using JSON (JavaScript Object Notation) to support future massive data expansion and interchanges. We firstly propose a series of rules for the mapping from VCF and OWL files to JSON files, and then present rule-based algorithms for transforming VCF-based genetic variants and OWL-based biological ontologies into JSON objects. On this basis, we introduce effective approaches of integrating the mapped JSON files in MongoDB. Finally, we complement this work with a set of experiments to show the performance of our proposed approaches. The source code of the proposed approaches could be freely available at https://github.com/lyotvincent/AJIA.

NeoPeptide: an immunoinformatic database of T-cell-defined neoantigens

Therapeutic vaccines represent a promising immunotherapeutic modality against cancer. Discovery and validation of antigens is the key to develop effective anti-cancer vaccines. Neoantigens, arising from somatic mutations in individual cancers, are considered as ideal cancer vaccine targets because of their immunogenicity and lack of expression in normal tissues. However, only few databases support convenient access to these neoantigens for use in vaccines. To address this gap, we developed a web-accessible database, called NeoPeptide, which contains most of the important characteristics of neoantigens (such as mutation site, subunit sequence, major histocompatibility complex restriction) derived from published literature and other immunological resources. NeoPeptide also provides links to resources for further characterization of the novel features of these neoantigens. NeoPeptide will be regularly updated with newly identified and published neoantigens. Our work will help researchers in identifying neoantigens in different cancers and hasten the search for appropriate cancer vaccine candidates.