Author

Anju Lulla

University of North Carolina at Chapel Hill

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Research Focus:batch correction / integration· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:metabolomics· 1 Assay:metagenomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Katie A. MeyeriD· 2 shared Angela Yu ZhangiD· 1 shared Anna PlantingaiD· 1 shared Anthony A. FodoriD· 1 shared Hongjiao LiuiD· 1 shared James Robert WhiteiD· 1 shared Jessica SprinklesiD· 1 shared Jun CheniD· 1 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersPhysiology

Katie A. MeyerORCID

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2 papers

Recent·Most cited

Individual variability in polyphenol metabolite production: A dietary challenge study

Jessica Sprinkles, Anju Lulla, Katie A. Meyer

This study examines variability in polyphenol metabolite production after a controlled dietary challenge and finds significant individual differences and low agreement between tertiles of metabolite output.

bioRxiv · Mar 20, 2025 · PreprintPhysiology

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