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. Bush, WS, Wheeler, N, Beaulieu-Jones, B, Darabos, C. Packaging Biocomputing Software to Maximize Distribution and Reuse. Pac Symp Biocomput 2020; 25 : 739-742. PubMed PMID:31797644 .
  2. Crawford, DC, Lin, J, Cooke Bailey, JN, Kinzy, T, Sedor, JR, O'Toole, JF, Bush, WS. Frequency of ClinVar Pathogenic Variants in Chronic Kidney Disease Patients Surveyed for Return of Research Results at a Cleveland Public Hospital. Pac Symp Biocomput 2020; 25 : 575-586. PubMed PMID:31797629 PubMed Central PMC6931908.
  3. Wheeler, NR, Benchek, P, Kunkle, BW, Hamilton-Nelson, KL, Warfe, M, Fondran, JR, Haines, JL, Bush, WS. Hadoop and PySpark for reproducibility and scalability of genomic sequencing studies. Pac Symp Biocomput 2020; 25 : 523-534. PubMed PMID:31797624 PubMed Central PMC6956992.
  4. Bis, JC, Jian, X, Kunkle, BW, Chen, Y, Hamilton-Nelson, KL, Bush, WS, Salerno, WJ, Lancour, D, Ma, Y, Renton, AE et al.. Correction: Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation. Mol. Psychiatry 2019; : . PubMed PMID:31636380 .
  5. Dumitrescu, L, Barnes, LL, Thambisetty, M, Beecham, G, Kunkle, B, Bush, WS, Gifford, KA, Chibnik, LB, Mukherjee, S, De Jager, PL et al.. Sex differences in the genetic predictors of Alzheimer's pathology. Brain 2019; 142 (9): 2581-2589. PubMed PMID:31497858 PubMed Central PMC6736148.
  6. Bush, WS, Cooke Bailey, JN, Beno, MF, Crawford, DC. Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines. Public Health Genomics 2019; 22 (1-2): 16-24. PubMed PMID:31454805 PubMed Central PMC6752968.
  7. Kunkle, BW, Grenier-Boley, B, Sims, R, Bis, JC, Damotte, V, Naj, AC, Boland, A, Vronskaya, M, van der Lee, SJ, Amlie-Wolf, A et al.. Author Correction: Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 2019; 51 (9): 1423-1424. PubMed PMID:31417202 .
  8. Gardner, OK, Wang, L, Van Booven, D, Whitehead, PL, Hamilton-Nelson, KL, Adams, LD, Starks, TD, Hofmann, NK, Vance, JM, Cuccaro, ML et al.. RNA editing alterations in a multi-ethnic Alzheimer disease cohort converge on immune and endocytic molecular pathways. Hum. Mol. Genet. 2019; 28 (18): 3053-3061. PubMed PMID:31162550 PubMed Central PMC6737295.
  9. Li, Y, Xiao, X, Bossé, Y, Gorlova, O, Gorlov, I, Han, Y, Byun, J, Leighl, N, Johansen, JS, Barnett, M et al.. Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development. Oncotarget 2019; 10 (19): 1760-1774. PubMed PMID:30956756 PubMed Central PMC6442994.
  10. Kunkle, BW, Grenier-Boley, B, Sims, R, Bis, JC, Damotte, V, Naj, AC, Boland, A, Vronskaya, M, van der Lee, SJ, Amlie-Wolf, A et al.. Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 2019; 51 (3): 414-430. PubMed PMID:30820047 PubMed Central PMC6463297.
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