WILLIAM S. BUSH, PHD, MS

Associate Director for Bioinformatics Research

William S. Bush, PhD, MS, is Associate Professor in the Department of Population and Quantitative Health Sciences and the Cleveland Institute for Computational Biology at Case Western Reserve University. Dr. Bush received his PhD at Vanderbilt University in Human Genetics in 2008 and then continued as a post-doctoral fellow in the Neurogenomics Training Program at Vanderbilt. Dr. Bush was recently named a Mt. Sinai Health Care Foundation Scholar. As a human geneticist and bioinformatician, Dr. Bush’s research interests include understanding the functional impact of genetic variation, developing statistical and bioinformatics approaches for integrating functional genomics knowledge into genetic analysis, and the use of electronic medical records for translational research.

Affiliations

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Featured Publications

Genetic analysis of biological pathway data through genomic randomization.

Yaspan BL, Bush WS, Torstenson ES, Ma D, Pericak-Vance MA, Ritchie MD, Sutcliffe JS, Haines JL,. Genome Wide Association Studies (GWAS) are a standard approach for large-scale common variation characterization and for identification of single loci predisposing to disease. However, due to issues of moderate sample sizes and particularly multiple testing correction, many variants of […]

Multivariate analysis of regulatory SNPs: empowering personal genomics by considering cis-epistasis and heterogeneity.

Turner SD, Bush WS,. Understanding how genetic variants impact the regulation and expression of genes is important for forging mechanistic links between variants and phenotypes in personal genomics studies. In this work, we investigate statistical interactions among variants that alter gene expression and identify 79 genes showing highly significant interaction effects consistent with genetic heterogeneity. […]

Genome simulation approaches for synthesizing in silico datasets for human genomics.

Ritchie MD, Bush WS,. Simulated data is a necessary first step in the evaluation of new analytic methods because in simulated data the true effects are known. To successfully develop novel statistical and computational methods for genetic analysis, it is vital to simulate datasets consisting of single nucleotide polymorphisms (SNPs) spread throughout the genome at […]

Visualizing SNP statistics in the context of linkage disequilibrium using LD-Plus.

Bush WS, Dudek SM, Ritchie MD,. Often in human genetic analysis, multiple tables of single nucleotide polymorphism (SNP) statistics are shown alongside a Haploview style correlation plot. Readers are then asked to make inferences that incorporate knowledge across these multiple sets of results. To better facilitate a collective understanding of all available data, we developed […]

Recent Publications

  1. Guo, Z, Duan, D, Tang, W, Zhu, J, Bush, WS, Zhang, L, Zhu, X, Jin, F, Feng, H. magpie: A power evaluation method for differential RNA methylation analysis in N6-methyladenosine sequencing. PLoS Comput Biol 2024; 20 (2): e1011875. PubMed PMID:38346081 PubMed Central PMC10890765.
  2. Leung, YY, Naj, AC, Chou, YF, Valladares, O, Schmidt, M, Hamilton-Nelson, K, Wheeler, N, Lin, H, Gangadharan, P, Qu, L et al.. Human whole-exome genotype data for Alzheimer's disease. Nat Commun 2024; 15 (1): 684. PubMed PMID:38263370 PubMed Central PMC10805795.
  3. Archer, DB, Eissman, JM, Mukherjee, S, Lee, ML, Choi, SE, Scollard, P, Trittschuh, EH, Mez, JB, Bush, WS, Kunkle, BW et al.. Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease. Alzheimers Dement 2024; 20 (2): 1268-1283. PubMed PMID:37985223 PubMed Central PMC10896586.
  4. Eissman, JM, Archer, DB, Mukherjee, S, Lee, ML, Choi, SE, Scollard, P, Trittschuh, EH, Mez, JB, Bush, WS, Kunkle, BW et al.. Sex-specific genetic architecture of late-life memory performance. Alzheimers Dement 2024; 20 (2): 1250-1267. PubMed PMID:37984853 .
  5. Wang, A, Shen, J, Rodriguez, AA, Saunders, EJ, Chen, F, Janivara, R, Darst, BF, Sheng, X, Xu, Y, Chou, AJ et al.. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants. Nat Genet 2023; 55 (12): 2065-2074. PubMed PMID:37945903 PubMed Central PMC10841479.
  6. Greenfest-Allen, E, Valladares, O, Kuksa, PP, Gangadharan, P, Lee, WP, Cifello, J, Katanic, Z, Kuzma, AB, Wheeler, N, Bush, WS et al.. NIAGADS Alzheimer's GenomicsDB: A resource for exploring Alzheimer's disease genetic and genomic knowledge. Alzheimers Dement 2024; 20 (2): 1123-1136. PubMed PMID:37881831 .
  7. Lee, WP, Choi, SH, Shea, MG, Cheng, PL, Dombroski, BA, Pitsillides, AN, Heard-Costa, NL, Wang, H, Bulekova, K, Kuzma, AB et al.. Association of Common and Rare Variants with Alzheimer's Disease in over 13,000 Diverse Individuals with Whole-Genome Sequencing from the Alzheimer's Disease Sequencing Project. medRxiv 2023; : . PubMed PMID:37693521 PubMed Central PMC10491367.
  8. Tejeda, M, Farrell, J, Zhu, C, Wetzler, L, Lunetta, KL, Bush, WS, Martin, ER, Wang, LS, Schellenberg, GD, Pericak-Vance, MA et al.. DNA from multiple viral species is associated with Alzheimer's disease risk. Alzheimers Dement 2024; 20 (1): 253-265. PubMed PMID:37578203 PubMed Central PMC10840621.
  9. Walters, S, Contreras, AG, Eissman, JM, Mukherjee, S, Lee, ML, Choi, SE, Scollard, P, Trittschuh, EH, Mez, JB, Bush, WS et al.. Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults. JAMA Neurol 2023; 80 (9): 929-939. PubMed PMID:37459083 PubMed Central PMC10352930.
  10. Grunin, M, Palmer, E, de Jong, S, Jin, B, Rinker, D, Moth, C, Capra, JA, Haines, JL, Bush, WS, den Hollander, AI et al.. Integrating Computational Approaches to Predict the Effect of Genetic Variants on Protein Stability in Retinal Degenerative Disease. Adv Exp Med Biol 2023; 1415 : 157-163. PubMed PMID:37440029 .
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