“We aim to develop novel computational tools and enhance availability and usage of open-source bioinformatics and statistical modelling platforms to advance capability in innovative and high-quality analysis of microbiome data.”
Additional expertise provided by Dr. Irina Dinu at the University of Alberta, and Dr. Robert Beiko and Dr. Morgan Langille at Dalhousie University.
Our experts are continuously developing new open-access computational tools to analyze microbiome data more accurately and efficiently, as well as posting relevant tutorials.
Get access to bioinformatics and data analysis support for microbiome researchers. Contact us for more details.
Bioinformatics.ca has resources for the bioinformatics community in Canada, including a lists of bioinformatics experts, job postings, education programs/workshops, and upcoming bioinformatics activities. See bioinformatics.ca on GitHub for workshops, repositories, and more.
QIIME 2 Forum is the official forum for the QIIME 2 community, providing user, developer, and technical support. QIIME 2 (Quantitative Insights Into Microbial Ecology 2) is a next-generation microbiome bioinformatics platform that is extensible, free, open source, and community developed.
Contact us if you don’t have access to these publications.
Bertelli et al. 2019. Microbial Genomic Island Discovery, Visualization and Analysis. Brief Bioinformatics. 20(5): 1685-1698.
Knight et al. 2018. Best practices for analysing microbiomes. Nat Rev Microbiol. 16: 410-422.
Peabody et al. 2015. Evaluation of Shotgun Metagenomics Sequence Classification Methods Using in silico and in vitro simulated communities. BMC Bioinformatics. 16(362): 1-19.
Basik et al. 2013. Biopsies: Next-Generation Biospecimens for Tailoring Therapy. Nat Rev Clin Oncol. 10: 437-450.
Kelly & Greenwood. 2013. A sequence of methodological changes due to sequencing. Curr Opin Allergy Clin Immunol. 13(5): 470-477.
Langille et al. 2010. Detecting Genomic Islands Using Bioinformatics Approaches. Nat Rev Microbiol. 8: 373-782.
Hamid et al. 2009. Data Integration in Genetics and Genomics: Methods and Challenges. Hum Genom Proteom. 2009(869093): 1-13.
