TriTrypDB: An integrated functional genomics resource for kinetoplastida.



Shanmugasundram, Achchuthan, Starns, David, Böhme, Ulrike, Amos, Beatrice, Wilkinson, Paul A, Harb, Omar S, Warrenfeltz, Susanne, Kissinger, Jessica C, McDowell, Mary Ann, Roos, David S
et al (show 2 more authors) (2023) TriTrypDB: An integrated functional genomics resource for kinetoplastida. PLoS neglected tropical diseases, 17 (1). e0011058-e0011058.

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Abstract

Parasitic diseases caused by kinetoplastid parasites are a burden to public health throughout tropical and subtropical regions of the world. TriTrypDB (https://tritrypdb.org) is a free online resource for data mining of genomic and functional data from these kinetoplastid parasites and is part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org). As of release 59, TriTrypDB hosts 83 kinetoplastid genomes, nine of which, including Trypanosoma brucei brucei TREU927, Trypanosoma cruzi CL Brener and Leishmania major Friedlin, undergo manual curation by integrating information from scientific publications, high-throughput assays and user submitted comments. TriTrypDB also integrates transcriptomic, proteomic, epigenomic, population-level and isolate data, functional information from genome-wide RNAi knock-down and fluorescent tagging, and results from automated bioinformatics analysis pipelines. TriTrypDB offers a user-friendly web interface embedded with a genome browser, search strategy system and bioinformatics tools to support custom in silico experiments that leverage integrated data. A Galaxy workspace enables users to analyze their private data (e.g., RNA-sequencing, variant calling, etc.) and explore their results privately in the context of publicly available information in the database. The recent addition of an annotation platform based on Apollo enables users to provide both functional and structural changes that will appear as 'community annotations' immediately and, pending curatorial review, will be integrated into the official genome annotation.

Item Type: Article
Uncontrolled Keywords: Kinetoplastida, Proteomics, Computational Biology, Genomics, Internet, Software, User-Computer Interface, Databases, Genetic
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 13 Feb 2023 08:49
Last Modified: 17 Mar 2023 17:22
DOI: 10.1371/journal.pntd.0011058
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3168372