Boyi Guo

Boyi Guo, PhD, MS

Languages spoken: Chinese, English

Academic Information

Departments Primary - Population Health Sciences

Academic Office Information

boyi.guo@utah.edu

Research Interests

  • Machine Learning/ Artifical Intelligence
  • Computational Biology
  • Spatial Omics
  • High Dimensional Data Analysis
  • Neurobiology
  • Neuropsychiatry

Dr. Boyi Guo is an Assistant Professor in the Biostatistics Division of Population Health Sciences Department at the University of Utah. He develops computational tools to integrate and analyze population-scale molecular and clinical datasets to uncover mechanisms behind complex diseases, such as psychiatric disorders and cancer. Before joining University of Utah, he earned his PhD in Biostatistics from the University of Alabama Birmingham and completed a postdoctoral fellowship at Johns Hopkins Bloomberg School of Public Health. His methodological and collaborative contribtions has been featured in journals including Nature Methods, Bioinformatics, and Science.

Education History

Fellowship Johns Hopkins Bloomberg School of Public Health
 Postdoctoral Fellow
Doctoral Training University of Alabama at Birmingham
 PhD
Graduate Training University of Illinois at Urbana-Champaign
 MS
Undergraduate University of Illinois at Urbana-Champaign
 BS
Undergraduate University of Illinois at Urbana-Champaign
 BS

Selected Publications

Journal Article

  1. Zhou H, Panwar P, Guo B, Hallinan C, Ghazanfar S, Hicks SC (2024). Spatial mutual nearest neighbors for spatial transcriptomics data. Bioinformatics, 41(8). (Read full article)
  2. Totty M, Hicks SC, Guo B (2025). SpotSweeper: spatially aware quality control for spatial transcriptomics. Nat Methods, 22(7), 1520-1530. (Read full article)
  3. Guo B, Ling W, Kwon SH, Panwar P, Ghazanfar S, Martinowich K, Hicks SC (2025). Integrating spatially-resolved transcriptomics data across tissues and individuals: Challenges and opportunities. Small Methods, e2401194. (Read full article)
  4. Shah K, Guo B, Hicks SC (2024). Addressing the mean-variance relationship in spatially resolved transcriptomics data with spoon. Biostatistics, 26(1). (Read full article)
  5. Shah KH, Guo B, Hicks SC (2024). Addressing the mean-variance relationship in spatially resolved transcriptomics data with spoon. bioRxiv.
  6. Totty M, Hicks SC, Guo B (2024). SpotSweeper: spatially-aware quality control for spatial transcriptomics. bioRxiv. (Read full article)
  7. Huuki-Myers LA, Spangler A, Eagles NJ, Montgomery KD, Kwon SH, Guo B, Grant-Peters M, Divecha HR, Tippani M, Sriworarat C, Nguyen AB, Ravichandran P, Tran MN, Seyedian A, PsychENCODE Consortium, Hyde TM, Kleinman JE, Battle A, Page SC, Ryten M, Hicks SC, Martinowich K, Collado-Torres L, Maynard KR, PsychENCODE Consortium (2024). A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex. Science, 384(6698), eadh1938. (Read full article)
  8. Malla G, Long DL, Cherrington A, Goyal P, Guo B, Safford MM, Khodneva Y, Cummings DM, McAlexander TP, DeSilva S, Judd SE, Hidalgo B, Levitan EB, Carson AP (2024). Neighborhood Disadvantage and Risk of Heart Failure: The Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Circ Cardiovasc Qual Outcomes, 17(3), e009867. (Read full article)
  9. Zhou H, Panwar P, Guo B, Hallinan C, Ghazanfar S, Hicks SC (2024). Spatial mutual nearest neighbors for spatial transcriptomics data. bioRxiv.
  10. Guo B, Huuki-Myers LA, Grant-Peters M, Collado-Torres L, Hicks SC (2023). escheR: unified multi-dimensional visualizations with Gestalt principles. Bioinform Adv, 3(1), vbad179. (Read full article)
  11. Lin X, Xiao HM, Liu HM, Lv WQ, Greenbaum J, Gong R, Zhang Q, Chen YC, Peng C, Xu XJ, Pan DY, Chen Z, Li ZF, Zhou R, Wang XF, Lu JM, Ao ZX, Song YQ, Zhang YH, Su KJ, Meng XH, Ge CL, Lv FY, Luo Z, Shi XM, Zhao Q, Guo BY, Yi NJ, Shen H, Papasian CJ, Shen J, Deng HW (2023). Gut microbiota impacts bone via Bacteroides vulgatus-valeric acid-related pathways. Nat Commun, 14(1), 6853. (Read full article)
  12. Bhave VM, Ament Z, Patki A, Gao Y, Kijpaisalratana N, Guo B, Chaudhary NS, Guarniz AG, Gerszten R, Correa A, Cushman M, Judd S, Irvin MR, Kimberly WT (2022). Plasma Metabolites Link Dietary Patterns to Stroke Risk. Ann Neurol, 93(3), 500-510. (Read full article)
  13. Guo B, Li L, Rudolph JE (2023). Statistical thinking in simulation design: a continuing conversation on the balancing intercept problem. ArXiv.
  14. Kamin Mukaz D, Guo B, Long DL, Judd SE, Plante TB, McClure LA, Wolberg AS, Zakai NA, Howard G, Cushman M (2022). D-dimer and the risk of hypertension: The REasons for Geographic And Racial Differences in Stroke Cohort Study. Res Pract Thromb Haemost, 7(1), 100016. (Read full article)
  15. Guo B, Jaeger BC, Rahman AKMF, Long DL, Yi N (2022). Spike-and-slab least absolute shrinkage and selection operator generalized additive models and scalable algorithms for high-dimensional data analysis. Stat Med, 41(20), 3899-3914. (Read full article)
  16. Peper KM, Guo B, Leann Long D, Howard G, Carson AP, Howard VJ, Judd SE, Zakai NA, Cherrington A, Cushman M, Plante TB (2021). C-reactive Protein and Racial Differences in Type 2 Diabetes Incidence: The REGARDS Study. J Clin Endocrinol Metab, 107(6), e2523-e2531. (Read full article)
  17. Long DL, Guo B, McClure LA, Jaeger BC, Tison SE, Howard G, Judd SE, Howard VJ, Plante TB, Zakai NA, Koh I, Cheung KL, Cushman M (2021). Biomarkers as MEDiators of racial disparities in risk factors (BioMedioR): Rationale, study design, and statistical considerations. Ann Epidemiol, 66, 13-19. (Read full article)
  18. Guo B, Yi N (2022). A scalable and flexible Cox proportional hazard model for high-dimensional survival prediction and functional selection. ArXiv.
  19. Guo B, Yi N (2022). The R Package BHAM: Fast and scalable Bayesian hierarchical additive model for high- dimensional data. ArXiv.
  20. Plante TB, Long DL, Guo B, Howard G, Carson AP, Howard VJ, Judd SE, Jenny NS, Zakai NA, Cushman M (2020). C-Reactive Protein and Incident Hypertension in Black and White Americans in the REasons for Geographic And Racial Differences in Stroke (REGARDS) Cohort Study. Am J Hypertens, 34(7), 698-706. (Read full article)
  21. Guo B, Holscher H, Auvil L, Welge M, Bushell C, Novotny J, Baer D, Burd N, Khan N, Zhu R (2021). Estimating Heterogeneous Treatment Effect on Multivariate Responses Using Random Forests. Stat Biosci, 15, 545–61.
  22. Cummings DM, Patil SP, Long DL, Guo B, Cherrington A, Safford MM, Judd SE, Howard VJ, Howard G, Carson AP (2021). Does the Association Between Hemoglobin A(1c) and Risk of Cardiovascular Events Vary by Residential Segregation? The REasons for Geographic And Racial Differences in Stroke (REGARDS) Study. Diabetes Care, 44(5), 1151-1158. (Read full article)
  23. Zhang X, Guo B, Yi N (2020). Zero-Inflated gaussian mixed models for analyzing longitudinal microbiome data. PLoS One, 15(11), e0242073. (Read full article)
  24. Seifert ME, Gaut JP, Guo B, Jain S, Malone AF, Geraghty F, Della Manna DL, Yang ES, Yi N, Brennan DC, Mannon RB (2019). WNT pathway signaling is associated with microvascular injury and predicts kidney transplant failure. Am J Transplant, 19(10), 2833-2845. (Read full article)
  25. Pendegraft AH, Guo B, Yi N (2019). Bayesian hierarchical negative binomial models for multivariable analyses with applications to human microbiome count data. PLoS One, 14(8), e0220961. (Read full article)
  26. Yi N, Tang Z, Zhang X, Guo B (2018). BhGLM: Bayesian hierarchical GLMs and survival models, with applications to genomics and epidemiology. Bioinformatics, 35(8), 1419-1421. (Read full article)
  27. Tang Z, Lei S, Zhang X, Yi Z, Guo B, Chen JY, Shen Y, Yi N (2019). Gsslasso Cox: a Bayesian hierarchical model for predicting survival and detecting associated genes by incorporating pathway information. BMC Bioinformatics, 20(1), 94. (Read full article)
  28. Zhang X, Pei YF, Zhang L, Guo B, Pendegraft AH, Zhuang W, Yi N (2018). Negative Binomial Mixed Models for Analyzing Longitudinal Microbiome Data. Front Microbiol, 9, 1683. (Read full article)
  29. Bashir M, Wee C, Memon N, Guo B (2017). Profiling cybersecurity competition participants: Self-efficacy, decision- making and interests predict effectiveness of competitions as a recruitment tool. Comput Secur, 65, 153-165.
  30. Bashir M, Lambert A, Guo B, Memon N, Halevi T (2015). Cybersecurity Competitions: The Human Angle. IEEE Secur Priv, 13(5), 74 - 79.

Abstract

  1. Peper KM, Guo B, Long L, Howard G, Carson AP, Howard VJ, Judd SE, Zakai NA, Cherrington A, Cushman M, Plante TB (2020). C-reactive Protein and Racial Differences in Type 2 Diabetes Incidence: Reasons for Geographic and Racial Differences in Stroke (REGARDS) [Abstract]. 141(Suppl_1), AP300.
  2. Subramaniam A, Guo B, Lobashevsky E, van der Pol W, Lefkowitz E, Morrow C, Owen J (2020). Association of the cervicovaginal microbiome with cervical shortening in women with prior spontaneous preterm birth [Abstract]. 222(1), S268-9.
  3. Subramaniam A, Guo B, Lobashevsky E, van der Pol W, Lefkowitz, E, Morrow C, Owen J (2020). Effect of intramuscular progesterone on the cervicovaginal microbiome in high-risk women with midtrimester cervical shortening [Abstract]. 222(1), S268.
  4. Subramaniam A, Guo B, Lobashevsky E, van der Pol W, Lefkowitz E, Morrow C, Szychowski JM, Yi N, Owen J (2020). Are cervicovaginal microbiome differences associated with cerclage success in high-risk women with cervical shortening? [Abstract]. 222(1), S123.
  5. Subramaniam A, Guo B, Lobashevsky E, van der Pol W, Lefkowitz E, Morrow C, Owen J (2020). Longitudinal changes in the cervicovaginal microbiome in high-risk women who experience midtrimester cervical shortening [Abstract]. 222(1), S73-4.
  6. Subramaniam A, Guo B, Wetta, L, Lobashevsky E, van der Pol W, Lefkowitz E, Owen J (2020). Association of cervicovaginal microbial changes with pro-and anti-inflammatory biomarkers in cervicovaginal fluid [Abstract]. 222(1), S15-6.
  7. Bashir M, Lambert A, Wee JMC, Guo B (2015). An examination of the vocational and psychological characteristics of cybersecurity competition participants [Abstract].

Other

  1. Guo B, Samorodnitsky S (2022). Keep your receipts: A guide for early-career statisticians to navigate conferences’ hidden curriculum. AmstatNews.
  2. Bashir M, Lambert A, Wee JMC, Guo B (2015). An examination of the vocational and psychological characteristics of cybersecurity competition participants.

Video/Film/CD/Web/Podcast

  1. Guo B (2025). spoon. Software, R package addresses the mean-variance relationship in spatially resolved transcriptomics data [Web]. Bioconductor. Available: https://www.bioconductor.org/packages/release/bioc/html/spoon.html.
  2. Guo B (2025). escheR. Software, R package built off of ggplot2 and the Gestalt principles to visualize multi-dimensional data in the 2D space (e.g. embedding or spatial visualizations) [Web]. Bioconductor. Available: https://www.bioconductor.org/packages/release/bioc/html/escheR.html.
  3. Guo B (2025). tpSVG. Software, R package to model gene expression of spatially resolved transcriptomics data using generalized geo-additive models [Web]. Bioconductor. Available: https://www.bioconductor.org/packages/release/bioc/html/tpSVG.html.
  4. Guo B (2024). SpotSweeper. Software, R package to identify outliers spot and large technical artifacts by calculating local mean and variance of standard QC metrics [Web]. Bioconductor. Available: https://www.bioconductor.org/packages/release/bioc/html/SpotSweeper.html.
  5. Guo B (2022). Calculating residential segregation indices with decennial US census data in an R reproducible workflow. Practice-Related Report [Web]. Available: https://github.com/boyiguo1/Tutorial-Residential_Segregation_Score.
  6. Guo B, Cui J (2021). Automating simulation studies with high-performance computing platform. Practice-Related Report [Web]. Available: https://github.com/boyiguo1/Tutorial-Sim_Cluster_Composer.
  7. Guo B (2021). R (C++)/MOTE.RF. Software R package to build random forests algorithm to infer treatment effect for multivariate outcome [Web]. GitHub. Available: https://github.com/boyiguo1/MOTE.RF/blob/master/NAMESPACE.
  8. Guo B (2020). R/BHAM. Software, R package to build scalable Bayesian hierarchical additive models using spike-and-slab priors for high-dimensional data analysis [Web]. GitHub. Available: https://github.com/boyiguo1/BHAM/blob/master/README.Rmd.
  9. Guo B (2019). R/TibbleOne. Software, Convenient framework to tabulate participant characteristics for epidemiology studies [Web]. GitHub. Available: https://github.com/bcjaeger/tibbleOne/.
  10. Guo B (2018). R/BhGLM. Software R package for fast-computing Bayesian Hierarchical GLMs and survival model [Web]. GitHub. Available: https://github.com/nyiuab/BhGLM.