Author

Lauren M. Harmon

Van Andel InstituteORCID 0000-0002-2248-0602Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Organism:human· 2 Research Focus:variant calling· 2 Research Focus:variant effect prediction· 2 Assay:bulk RNA-seq· 1 Assay:DNA methylation· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Timothy J. TricheiD· 2 shared Chloe C. LucidoiD· 1 shared Daniel Diniz De CarvalhoiD· 1 shared Eve GardneriD· 1 shared Hady W. SabraiD· 1 shared Hong WeniD· 1 shared J. Anthony BrandoniD· 1 shared John S. K. KauweiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersBioinformatics

Timothy J. TricheORCID

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Author profile →

3 papers

Recent·Most cited

Ramp sequence may explain synonymous variant association with Alzheimer's disease in the Paired Immunoglobulin-like Type 2 Receptor Alpha (PILRA)

Justin B. Miller, J. Anthony Brandon, Lauren M. Harmon, Hady W. Sabra, Chloe C. Lucido, Josue D. Gonzalez Murcia, Kayla A. Nations, Samuel H. Payne, Mark Ebbert, John S. K. Kauwe, Perry G. Ridge

The paper shows that a synonymous variant in PILRA decreases mRNA and protein levels by disrupting a ramp sequence, providing a biological mechanism for its association with Alzheimer's disease.

Biomedicines · Mar 18, 2025Peer-reviewedGenetics

bamSliceR: a Bioconductor package for rapid, cross-cohort variant analysis

Yizhou Peter Huang, Lauren M. Harmon, Eve Gardner, Xiaotu Ma, Josiah Harsh, Zhaoyu Xue, Hong Wen, Marcel Ramos, Sean R. Davis, Timothy J. Triche

bamSliceR enables rapid, cross-cohort variant analysis by extracting and analyzing aligned reads from GDC data, identifying clinically relevant variants in leukemia cohorts.

Bioinformatics Advances · Dec 26, 2024Peer-reviewedBioinformatics

Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls

Samantha L. Wilson, Shu Yi Shen, Lauren M. Harmon, Justin Burgener, Timothy J. Triche, Scott Victor Bratman, Daniel Diniz De Carvalho, Michael M. Hoffman

This paper introduces synthetic spike-in controls for cfMeDIP-seq to enable accurate and reproducible quantification of DNA methylation, reducing batch effects and technical biases.

Cell Reports Methods · Sep 1, 2022Peer-reviewedGenomics