D Supplemental figures

Figure D.1: Fold changes in the mean efficiency within and between women in the MOMS-PI study.

$A bias-sensivity analysis can be performed to examine how sensitive the results of a DA analysis are to assumptions about taxonomic bias in community measurements. The figure shows the results of a bias-sensitivity analysis used to study the effect of bias on the association of Gardnerella vaginalis and preterm birth that was investigated by Callahan et al. (2017). 100 random efficiency vectors were drawn at 6 different bias strengths (quantified by the variance in log efficiency, $\sigma_{e}^{2}$). Each efficiency vector was used to calibrate the MGS profiles and perform a DA association test of G. vaginalis versus the host’s preterm birth outcome; regression coefficients $\hat \beta$ indicate the increase of average logit proportion of G. vaginalis in women who experienced preterm birth.$

Figure D.2: A bias-sensivity analysis can be performed to examine how sensitive the results of a DA analysis are to assumptions about taxonomic bias in community measurements. The figure shows the results of a bias-sensitivity analysis used to study the effect of bias on the association of Gardnerella vaginalis and preterm birth that was investigated by Callahan et al. (2017). 100 random efficiency vectors were drawn at 6 different bias strengths (quantified by the variance in log efficiency, $\sigma_{e}^{2}$). Each efficiency vector was used to calibrate the MGS profiles and perform a DA association test of G. vaginalis versus the host’s preterm birth outcome; regression coefficients $\hat \beta$ indicate the increase of average logit proportion of G. vaginalis in women who experienced preterm birth.

References

Callahan, Benjamin J, Daniel B DiGiulio, Daniela S Aliaga Goltsman, Christine L Sun, Elizabeth K Costello, Pratheepa Jeganathan, Joseph R Biggio, et al. 2017. “Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women.” Proc. Natl. Acad. Sci. U. S. A. 114 (37): 9966–71. https://doi.org/10.1073/pnas.1705899114.