Author

Anna Plantinga

Williams CollegeORCID 0000-0001-6281-7727Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metagenomics· 3 Approach:statistical model· 3 Research Focus:batch correction / integration· 1 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Hongjiao LiuiD· 3 shared Michael C. WuiD· 3 shared Ni ZhaoiD· 3 shared Wodan LingiD· 3 shared Angela Yu ZhangiD· 2 shared Anju Lulla· 1 shared Anthony A. FodoriD· 1 shared Hoseung Song· 1 shared

Activity by Year

2021-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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3 shared papersBioinformatics

Hongjiao LiuORCID

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Author profile →

3 papers

Recent·Most cited

Constructing microbiome co-occurrence networks with confidence: A conditional, nonparametric, inference-based approach

Hoseung Song, Yunhua Xiang, Hongjiao Liu, Wodan Ling, Anna Plantinga, Sujatha Srinivasan, Yuzheng Dun, Ni Zhao, Shan Sun, Stephanie Mulherin Engel, Noah Simon, Michael C. Wu

The paper introduces a nonparametric method to construct microbiome co-occurrence networks with confidence, improving network recovery by accounting for conditional associations and providing statistical inference.

bioRxiv · Sep 1, 2026 · PreprintBioinformatics

Kernel-based genetic association analysis for microbiome phenotypes identifies host genetic drivers of beta-diversity

Hongjiao Liu, Wodan Ling, Xing Hua, Jee‐Young Moon, Jessica S Williams-Nguyen, Xiang Zhan, Anna Plantinga, Ni Zhao, Angela Yu Zhang, Rob D. Knight, Qibin Qi, Robert David Burk, Robert C. Kaplan, Michael C. Wu

The paper introduces a kernel-based method to identify host genetic variants associated with microbiome beta-diversity, finding immunity-related genes influence gut microbiota composition.

bioRxiv · Oct 15, 2021 · PreprintGenomics

Batch effects removal for microbiome data via conditional quantile regression (ConQuR)

Wodan Ling, Ni Zhao, Anju Lulla, Anna Plantinga, Weijia Fu, Angela Yu Zhang, Hongjiao Liu, Zhigang Li, Jun Chen, Timothy W. Randolph, Wei Li Adeline Koay, James Robert White, Lenore J. Launer, Anthony A. Fodor, Katie A. Meyer, Michael C. Wu

This paper introduces ConQuR, a method to remove batch effects in microbiome data by using conditional quantile regression, demonstrating its effectiveness in preserving signals and improving analysis.

bioRxiv · Sep 23, 2021 · PreprintBioinformatics