Author

Amarise Little

Fred Hutch Cancer CenterORCID 0009-0000-2618-7916Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:metabolomics· 1 Assay:metagenomics· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Michael C. WuiD· 2 shared Ni ZhaoiD· 2 shared Wodan LingiD· 2 shared Angela ZhangiD· 1 shared Dong D. WangiD· 1 shared Jee‐Young MooniD· 1 shared Jessica S Williams-NguyeniD· 1 shared Katie Marie CampbelliD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersBioinformatics

Michael C. WuORCID

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2 papers

Recent·Most cited

BioinformaticsPatternsPeer-reviewedJan 1, 2026

Detecting Clinically Relevant Topological Structures in Multiplexed Spatial Proteomics Imaging Using TopKAT

Sarah Samorodnitsky, Katie Marie Campbell, Amarise Little…·Michael C. Wu

This paper introduces TopKAT, a topology-based method to detect associations between spatial cell structures and clinical outcomes in spatial proteomics data.

2 citationstop 5%

humanspatial transcriptomics

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BioinformaticsbioRxivPreprintJun 14, 2024

Weighted variance component test for the integrative multi-omics analysis of microbiome data

Angela Zhang, Wodan Ling, Amarise Little…·Michael C. Wu

The paper introduces a weighted variance components framework to integrate metagenomic and metabolomic data for pathway analysis, showing improved power while controlling type I error.

DOI 10.1101/2024.06.14.599073

metagenomicsmetabolomics

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