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. 2015 Apr 8;16(1):67. doi: 10.1186/s13059-015-0637-x

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© Morgan et al.; licensee BioMed Central. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Results of multivariate linear modeling. Principal component analysis was used to reduce the data into nine gPCs and cPCs that explained 50% of total transcriptional and microbial variation. The top six loadings for each cPC (left) and cPC (middle) are shown; orange and blue indicate increases or decreases in expression, respectively. (Right) MaAsLin [5,28] was used for multivariate linear analysis of associations between cPCs and gPCs while controlling for the effects of inflammation, tissue location, and antibiotic use. Black/gray scale corresponds to the significance of the association, while blue / orange corresponds to the direction. See also Additional file 5.