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Comment
. 2021 Jan;18(1):37-39.
doi: 10.1038/s41592-020-01006-1. Epub 2021 Jan 4.

Examining microbe-metabolite correlations by linear methods

Thomas P Quinn  1 , Ionas Erb  2
Affiliations
Comment

Examining microbe-metabolite correlations by linear methods

Thomas P Quinn et al. Nat Methods. 2021 Jan.
No abstract available

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Comment in

  • Reply to: Examining microbe-metabolite correlations by linear methods.
    Morton JT, McDonald D, Aksenov AA, Nothias LF, Foulds JR, Quinn RA, Badri MH, Swenson TL, Van Goethem MW, Northen TR, Vazquez-Baeza Y, Wang M, Bokulich NA, Watters A, Song SJ, Bonneau R, Dorrestein PC, Knight R. Morton JT, et al. Nat Methods. 2021 Jan;18(1):40-41. doi: 10.1038/s41592-020-01007-0. Epub 2021 Jan 4. Nat Methods. 2021. PMID: 33398188 No abstract available.

Comment on

  • Learning representations of microbe-metabolite interactions.
    Morton JT, Aksenov AA, Nothias LF, Foulds JR, Quinn RA, Badri MH, Swenson TL, Van Goethem MW, Northen TR, Vazquez-Baeza Y, Wang M, Bokulich NA, Watters A, Song SJ, Bonneau R, Dorrestein PC, Knight R. Morton JT, et al. Nat Methods. 2019 Dec;16(12):1306-1314. doi: 10.1038/s41592-019-0616-3. Epub 2019 Nov 4. Nat Methods. 2019. PMID: 31686038 Free PMC article.

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    1. Yachida, S. et al. Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer. Nat. Med. 25, 968–976 (2019). - DOI
    1. Fernandes, A. D. et al. Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis. Microbiome 2, 15 (2014). - DOI
    1. Lovell, D., Pawlowsky-Glahn, V., Egozcue, J. J., Marguerat, S. & Bähler, J. Proportionality: a valid alternative to correlation for relative data. PLoS Comput. Biol. 11, e1004075 (2015).

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