Author

Ellen McRae Greytak

Virginia EnergyORCID 0000-0002-1935-7515Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:polygenic risk· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Janet Cady· 2 shared Steven L. Armentrout· 2 shared Carlos CruchagaiD· 1 shared Charla K. MarshalliD· 1 shared Erin M. GordeniD· 1 shared James O’Connor· 1 shared Kimberly Sturk‐AndreaggiiD· 1 shared Sarah E. CarlsoniD· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Janet Cady

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2 papers

Recent·Most cited

Genetic & Genomic MedicinemedRxivPreprintFeb 10, 2023

Epistatic Features and Machine Learning Improve Alzheimer's Risk Prediction Over Polygenic Risk Scores

Stephen Hermes, Janet Cady, Steven L. Armentrout…·The Alzheimer’s Disease Neuroimaging Initiative

This study develops a paragenic risk score that improves Alzheimer's disease risk prediction by incorporating epistatic interactions and machine learning, outperforming traditional polygenic risk scores.

3 citations

humanGWAS summary statistics

𝕏 PostBluesky

GenomicsForensic Science International GeneticsPeer-reviewedNov 23, 2021

Extended kinship analysis of historical remains using SNP capture

Erin M. Gorden, Ellen McRae Greytak, Kimberly Sturk‐Andreaggi…·Charla K. Marshall

This study uses SNP capture panels to analyze degraded historical DNA samples and estimate kinship up to 4th degree relatives with varying success based on panel size.

66 citationstop 2%

whole-genome sequencingstatistical model

𝕏 PostBluesky