Species abundance information improves sequence taxonomy classification accuracy - Qiita data

Research datakeyboard_double_arrow_right Dataset 25 Jan 2019Publisher:ZenodoFunded by:NIH | Objectives, Partnership I..., NIH | Analysis of the Roles of ..., NHMRC | Robust bioinformatics for... +1 projects

Authors: Kaehler, Benjamin D; Bokulich, Nicholas A;

doi: 10.5281/zenodo.2548898 , 10.5281/zenodo.2548899

Species abundance information improves sequence taxonomy classification accuracy - Qiita data

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Abstract

QIIME 2 Artifacts containing microbiome samples, organised by EMPO 3 classification. Used to test q2-clawback. Downloaded from Qiita. Draws from the following Qiita study ids: 11113[1], 11444, 1716, 10369[2], 990[3], 2080, 1713, 894, 1289, 1883, 1673, 1288, 10353, 2192[4], 10323, 678, 1773, 662, 1799, 864, 1481, 1024[5], 1064, 2182, 10934, 1674, 1795[6], 10273, 10283[7], 10422[8], 804, 10308, 1056[9], 2382[5], 1240, 889, 1041, 1717, 1222, 11149, 11669, 807[10], 10245, 1711, 1721, 910, 1001, 895, 550[11], 1747[12], 713[13], 755, 861, 958[14], 11161[15], 11154[16], 945, 723, 1715, 1714, 10798. References 1. Schulfer, A. F. et al. Nat Microbiol 3, 234–242 (2017). 2. Ruhe, J. et al. Front Plant Sci 7 (2016). 3. O'Brien, S. L. et al. Environ Microbiol 18, 2039–2051 (2016). 4. Lax, S. et al. Science 345, 1048–1052 (2014). 5. Zarraonaindia, I. et al. mBio 6 (2015). 6. Navas-Molina, J. A. et al. in Methods Enzymol 371–444 (2013). 7. Fang, X. et al. Front Microbiol 9 (2018). 8. Tripathi, A. et al. mSystems 3 (2018). 9. Delsuc, F. et al. Mol Ecol 23, 1301–1317 (2013). 10. Gibbons, S. M. et al. PLoS ONE 9, e97435 (2014). 11. Caporaso, J. G. et al. Genome Biol 12, R50 (2011). 12. Hyde, E. R. et al. mSystems 1 (2016). 13. Brazelton, W. J., Nelson, B. & Schrenk, M. O. Front Microbiol 2 (2012). 14. Vitaglione, P. et al. Am J Clin Nutr 101, 251–261 (2014). 15. Spirito, C. M., Marzilli, A. M. & Angenent, L. T. Environ Sci Technol 52, 13438–13447 (2018). 16. Pham, V. T. H. et al. Sci Rep 7 (2017).

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