This repository provides the R function for the paper:
Song, H., Ling, W., Zhao, N., Plantinga, A.M., Broedlow, C.A., Klatt, N.R., Hensley-McBain, T., Wu, M.C. (2023).
Accommodating multiple potential normalizations in microbiome associations studies.
BMC Bioinformatics, 24(1):22.
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The main function,
omni(), provides the omnibus p-value by combining popular normalization strategies, such as none, rarefaction, TSS, CSS, and CLR, based on the Cauchy combination test (Liu et al., 2020). -
The main function utilizes association testing methods: linear regression, ZINQ proposed by Ling et al. (2021), and QRank proposed by Song et al. (2017), which are have been shown to consistently protect type I error and do not depend on the particular choice of normalization.
- Liu, Y., Xie, J.: Cauchy combination test: a powerful test with analytic p-value calculation under arbitrary dependency structures. Journal of the American Statistical Association 115(529), 393–402 (2020)
- Song, X., Li, G., Zhou, Z., Wang, X., Ionita-Laza, I., Wei, Y.: Qrank: a novel quantile regression tool for eqtl discovery. Bioinformatics 33(14), 2123–2130 (2017)
- Ling, W., Zhao, N., Plantinga, A.M., Launer, L.J., Fodor, A.A., Meyer, K.A., Wu, M.C.: Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (zinq). Microbiome 9(1), 1–19 (2021)