Batch effects removal for microbiome data via conditional quantile regression

Batch effects removal for microbiome data via conditional quantile regression

Here, the authors present ConQuR, a conditional quantile regression method that removes microbiome batch effects through non-parametric modeling of complex microbial read counts, while preserving the signals of interest.

Bibliographic Details
Main Authors: Wodan Ling, Jiuyao Lu, Ni Zhao, Anju Lulla, Anna M. Plantinga, Weijia Fu, Angela Zhang, Hongjiao Liu, Hoseung Song, Zhigang Li, Jun Chen, Timothy W. Randolph, Wei Li A. Koay, James R. White, Lenore J. Launer, Anthony A. Fodor, Katie A. Meyer, Michael C. Wu
Format: Article
Language:English
Published: Nature Portfolio 2022-09-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-022-33071-9

Internet

https://doi.org/10.1038/s41467-022-33071-9

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