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PICRUSt2 for prediction of metagenome functions

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Fig. 1: PICRUSt2 algorithm.
Fig. 2: PICRUSt2 performance characteristics.
Fig. 3: PICRUSt2 accurately predicts MetaCyc pathways and phenotypes for characterizing overall environments.

Data availability

The repository at includes the processed data files that can be used to re-generate the figures and findings in this paper. The accession codes for all sequencing data used in this study are listed in the Supplementary Methods.

Code availability

PICRUSt2 is available at The Python and R code used for the analyses and database construction described in this paper are available online at


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We thank Zhenjiang Xu and Amy Chen for providing us access to data files used for testing and the default reference database. We also thank Heather McIntosh for help designing the pipeline flowchart. G.M.D. is funded by an NSERC CGS-D scholarship. V.J.M. is funded by an NIH/NIAAA Ruth L. Kirschstein National Research Service Award (F30 AA026527). J.R.Z. is supported by NSF IOS CAREER grant 1942647. S.Y.N. is funded by an NSERC Discovery Grant. C.H. is funded in part by NIH NIDDK grants U54DK102557 and R24DK110499. M.G.I.L. is funded by an NSERC Discovery Grant and an NSERC Collaborative Research Development with co-funding from GlaxoSmithKline to M.G.I.L. and J.R.B.

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Correspondence to Morgan G. I. Langille.

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Editorial note: This article has been peer reviewed.

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Description: Supplementary Methods, Supplementary Results, Supplementary Figs. 117 and Supplementary Tables 1–4

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Douglas, G.M., Maffei, V.J., Zaneveld, J.R. et al. PICRUSt2 for prediction of metagenome functions. Nat Biotechnol 38, 685–688 (2020).

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