Abstract
The huge amount of genomic and transcriptomic data obtained to characterize human diversity can also be exploited to indirectly gather information on the human microbiome. Here we present the pipeline QmihR designed to identify and quantify the abundance of known microbiome communities and to search for new/rare pathogenic species in RNA-seq datasets. We applied QmihR to 36 RNA-seq tumor tissue samples from Ukrainian gastric carcinoma patients available in TCGA, in order to characterize their microbiome and check for efficiency of the pipeline. The microbes present in the samples were in accordance to published data in other European datasets, and the independent BLAST evaluation of microbiome-aligned reads confirmed that the assigned species presented the highest BLAST match-hits. QmihR is available at GitHub (https://github.com/Pereira-lab/QmihR).
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Acknowledgements
We wish to thank TCGA for the access provided to the protected data used in this work. Funds were guaranteed by the project “Advancing cancer research: from basic knowledge to application”; NORTE-01-0145-FEDER-000029; “Projetos Estruturados de I&D&I”, funded by Norte 2020 – Programa Operacional Regional do Norte. I3S is financed by FEDER - Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 - Competitiveness and Internationalization Operational Programme (POCI), Portugal 2020, and by Portuguese funds through FCT/Ministério da Ciência, Tecnologia e Inovação in the framework of the project “Institute for Research and Innovation in Health Sciences” (POCI-01-0145-FEDER-007274).
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Cavadas, B., Ferreira, J., Camacho, R., Fonseca, N.A., Pereira, L. (2017). QmihR: Pipeline for Quantification of Microbiome in Human RNA-seq. In: Fdez-Riverola, F., Mohamad, M., Rocha, M., De Paz, J., Pinto, T. (eds) 11th International Conference on Practical Applications of Computational Biology & Bioinformatics. PACBB 2017. Advances in Intelligent Systems and Computing, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-60816-7_21
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DOI: https://doi.org/10.1007/978-3-319-60816-7_21
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