Interests

  • Machine learning and predictive modeling
  • High-dimensional “Big Data”
  • Variable selection
  • Multi-omics cancer data integration
  • Robust nonparametric statistics

Publications

1. Patel, Y., Zhu, C., Yamaguchi, T. N., … Boutros, P. C. (2026). Metapipeline-DNA: A comprehensive germline and somatic genomics nextflow pipeline. Cell Reports Methods, 6(3), 101340. https://doi.org/10.1016/j.crmeth.2026.101340
2. Zeltser, N., Dang, R. M. A., Hugh-White, R., … Boutros, P. C. (2025). ApplyPolygenicScore: An r package for applying polygenic risk score models. Genetics in Medicine Open, 3, 103467. https://doi.org/10.1016/j.gimo.2025.103467
3. Jones, L. W., Lavery, J. A., Tsai, B. L., … Boutros, P. C. (2025). A co-clinical trial of exercise therapy in breast cancer prevention. Clinical Cancer Research, 31(16), 3377–3387. https://doi.org/10.1158/1078-0432.ccr-24-4298
4. Xu, X., Zhu, H., Hugh-White, R., … He, H. H. (2025). The landscape of N6-methyladenosine in localized primary prostate cancer. Nature Genetics, 57(4), 934–948. https://doi.org/10.1038/s41588-025-02128-y
5. Tohi, Y., Sahrmann, J. M., Arbet, J., … Boutros, P. C. (2025). De-escalation of monitoring in active surveillance for prostate cancer: Results from the GAP3 consortium. European Urology Oncology, 8(2), 347–354. https://doi.org/10.1016/j.euo.2024.07.006
6. Lippitt, W., Carlson, N. E., Arbet, J., … Kechris, K. (2024). Limitations of clustering with PCA and correlated noise. Journal of Statistical Computation and Simulation, 94(10), 2291–2319. https://doi.org/10.1080/00949655.2024.2329976
7. Weiner, A. B., Agrawal, R., Wang, N. K., … Reiter, R. E. (2024). Molecular hallmarks of prostate-specific membrane antigen in treatment-naïve prostate cancer. European Urology, 86(6), 579–587. https://doi.org/10.1016/j.eururo.2024.09.005
8. Ni, K., Rogowitz, E., Farahmand, A. K., … Saxon, D. R. (2024). Weight loss outcomes in a veterans affairs pharmacotherapy-based weight management clinic. Journal of the Endocrine Society, 8(5). https://doi.org/10.1210/jendso/bvae042
9. Greca, A. L., Grau, L., Arbet, J., … Kitahara, C. M. (2023). Anthropometric, dietary, and lifestyle factors and risk of advanced thyroid cancer: The NIH‐AARP diet and health cohort study. Clinical Endocrinology, 99(6), 586–597. https://doi.org/10.1111/cen.14970
10. Gamallat, Y., Choudhry, M., Li, Q., … Bismar, T. A. (2023). Serrate RNA effector molecule (SRRT) is associated with prostate cancer progression and is a predictor of poor prognosis in lethal prostate cancer. Cancers, 15(10), 2867. https://doi.org/10.3390/cancers15102867
11. Chan, T. W., Dodson, J. P., Arbet, J., … Xiao, X. (2022). Single-cell analysis in lung adenocarcinoma implicates RNA editing in cancer innate immunity and patient prognosis. Cancer Research, 83(3), 374–385. https://doi.org/10.1158/0008-5472.can-22-1062
12. Okamoto, Y., Devoe, S., Seto, N., … Demoruelle, M. K. (2021). Association of sputum neutrophil extracellular trap subsets with IgA anti–citrullinated protein antibodies in subjects at risk for rheumatoid arthritis. Arthritis &Amp; Rheumatology, 74(1), 38–48. https://doi.org/10.1002/art.41948
13. Lin, N. W., Arbet, J., Mroz, M. M., … Maier, L. A. (2022). Clinical phenotyping in sarcoidosis using cluster analysis. Respiratory Research, 23(1). https://doi.org/10.1186/s12931-022-01993-z
14. Grau, L., Arbet, J., Ostendorf, D. M., … Creasy, S. A. (2022). Creating an algorithm to identify indices of sleep quantity and quality from a wearable armband in adults. Sleep Science, 15(03), 279–287. https://doi.org/10.5935/1984-0063.20220052
15. Creasy, S. A., Ostendorf, D. M., Blankenship, J. M., … Catenacci, V. A. (2022). Effect of sleep on weight loss and adherence to diet and physical activity recommendations during an 18-month behavioral weight loss intervention. International Journal of Obesity, 46(8), 1510–1517. https://doi.org/10.1038/s41366-022-01141-z
16. Wood, C., Arbet, J., Amura, C. R., … Anderson, J. (2021). Multicenter study evaluating nitrous oxide use for labor analgesia at high- and low-altitude institutions. Anesthesia &Amp; Analgesia, 134(2), 294–302. https://doi.org/10.1213/ane.0000000000005712
17. Rosenthal, L., Lee, S., Jenkins, P., … Nodine, P. (2021). A survey of mental health in graduate nursing students during the COVID-19 pandemic. Nurse Educator, 46(4), 215–220. https://doi.org/10.1097/nne.0000000000001013
18. Reed, S. M., Arbet, J., & Staubli, L. (2021). Clinical nurse specialists in the united states registered with a national provider identifier. Clinical Nurse Specialist, 35(3), 119–128. https://doi.org/10.1097/nur.0000000000000592
19. Arbet, J., Zhuang, Y., Litkowski, E., … Kechris, K. (2021). Comparing statistical tests for differential network analysis of gene modules. Frontiers in Genetics, 12. https://doi.org/10.3389/fgene.2021.630215
20. Nodine, P. M., Arbet, J., Jenkins, P. A., … Hoon, S. (2021). Graduate nursing student stressors during the COVID-19 pandemic. Journal of Professional Nursing, 37(4), 721–728. https://doi.org/10.1016/j.profnurs.2021.04.008
21. Thomas, E. A., Zaman, A., Cornier, M.-A., … Rynders, C. A. (2020). Later meal and sleep timing predicts higher percent body fat. Nutrients, 13(1), 73. https://doi.org/10.3390/nu13010073
22. Arbet, J., Brokamp, C., Meinzen-Derr, J., … Spratt, H. M. (2020). Lessons and tips for designing a machine learning study using EHR data. Journal of Clinical and Translational Science, 5(1). https://doi.org/10.1017/cts.2020.513
23. Ramakrishnan, V. R., Arbet, J., Mace, J. C., … Smith, T. L. (2021). Predicting olfactory loss in chronic rhinosinusitis using machine learning. Chemical Senses, 46. https://doi.org/10.1093/chemse/bjab042
24. Ostendorf, D. M., Blankenship, J. M., Grau, L., … Catenacci, V. A. (2021). Predictors of long‐term weight loss trajectories during a behavioral weight loss intervention: An exploratory analysis. Obesity Science &Amp; Practice, 7(5), 569–582. https://doi.org/10.1002/osp4.530
25. Schmanski, A., Roberts, E., Coors, M., … Taylor, M. R. G. (2020). Research participant understanding and engagement in an institutional, self‐consent biobank model. Journal of Genetic Counseling, 30(1), 257–267. https://doi.org/10.1002/jgc4.1316
26. Carpenter, C. M., Frank, D. N., Williamson, K., … Kroehl, M. E. (2021). tidyMicro: A pipeline for microbiome data analysis and visualization using the tidyverse in r. BMC Bioinformatics, 22(1). https://doi.org/10.1186/s12859-021-03967-2
27. Arbet, J., McGue, M., & Basu, S. (2020). A robust and unified framework for estimating heritability in twin studies using generalized estimating equations. Statistics in Medicine, 39(27), 3897–3913. https://doi.org/10.1002/sim.8564
28. Coleman-Minahan, K., Sheeder, J., Arbet, J., …. (2020). Interest in medication and aspiration abortion training among colorado nurse practitioners, nurse midwives, and physician assistants. Women’s Health Issues, 30(3), 167–175. https://doi.org/10.1016/j.whi.2020.02.001
29. Gance-Cleveland, B., Linton, A., Arbet, J., … Sylvain, G. (2020). Predictors of overweight and obesity in childhood cancer survivors. Journal of Pediatric Oncology Nursing, 37(3), 154–162. https://doi.org/10.1177/1043454219897102
30. James-Allan, L. B., Arbet, J., Teal, S. B., … Jansson, T. (2019). Insulin stimulates GLUT4 trafficking to the syncytiotrophoblast basal plasma membrane in the human placenta. The Journal of Clinical Endocrinology &Amp; Metabolism, 104(9), 4225–4238. https://doi.org/10.1210/jc.2018-02778
31. Grinde, K. E., Arbet, J., Green, A., … Tintle, N. (2017). Illustrating, quantifying, and correcting for bias in post-hoc analysis of gene-based rare variant tests of association. Frontiers in Genetics, 8. https://doi.org/10.3389/fgene.2017.00117
32. Arbet, J., McGue, M., Chatterjee, S., …. (2017). Resampling-based tests for lasso in genome-wide association studies. BMC Genetics, 18(1). https://doi.org/10.1186/s12863-017-0533-3
33. Greco, B., Hainline, A., Arbet, J., … Tintle, N. (2015). A general approach for combining diverse rare variant association tests provides improved robustness across a wider range of genetic architectures. European Journal of Human Genetics, 24(5), 767–773. https://doi.org/10.1038/ejhg.2015.194