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• W3012243374 abstract "Abstract Key aspects of microbiome research are accurate identification of taxa followed by the profiling of their functionality. Amplicon profiling based on the 16S ribosomal DNA sequence is a ubiquitous technique to identify and profile the abundances of the various taxa. However, it does not provide information on their encoded functionality. Predictive tools which can accurately extrapolate the functional information of a microbiome based on taxonomic profile composition is essential. At present the applicability of these tools is however limited due to requirement of reference genomes from known species. We present IPCO (Inference of Pathways from Co-variance analysis), a new method of inferring functionality for 16S-based microbiome profiles independent of reference genomes. IPCO utilises the biological co-variance observed between paired taxonomic and functional profiles and co-varies it with the queried dataset. It outperforms other established methods both in terms of sample and feature profile prediction. Validation results confirmed that IPCO can replicate observed biological signals seen within shotgun and metabolite profiles. Comparative analysis of predicted functionality profiles with other popular 16S-based functional prediction tools indicates significantly lower performance with predicted functionality showing little to no correlation with paired shotgun features across samples. IPCO is implemented in R and available from https://github.com/IPCO-Rlibrary/IPCO ." @default.
• W3012243374 created "2020-03-23" @default.
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• W3012243374 date "2019-06-28" @default.
• W3012243374 modified "2023-10-11" @default.
• W3012243374 title "IPCO: Inference of Pathways from Co-variance analysis" @default.
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• W3012243374 doi "https://doi.org/10.1101/686923" @default.
• W3012243374 hasPublicationYear "2019" @default.
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