Publications

Trainees’ names are bolded and italicized.

Statistical Methodology

  1. P. Boileau, H. Zaki, G. Lileikyte, N. Nielsen, P. R. Lawler, and M. E. Schnitzer. “Assumption-Lean Differential Variance Inference for Heterogeneous Treatment Effect Detection”. Submitted (2026+). DOI: 10.48550/ARXIV.2512.03254. https://arxiv.org/abs/2512.03254.

  2. P. Boileau, N. Leng, and S. Dudoit. “Guidance on individualized treatment rule estimation in high dimensions”. In: The International Journal of Biostatistics (May. 2025). ISSN: 1557-4679. DOI: 10.1515/ijb-2024-0005. http://dx.doi.org/10.1515/ijb-2024-0005.

  3. P. Boileau, N. Leng, N. S. Hejazi, M. van der Laan, and S. Dudoit. “A nonparametric framework for treatment effect modifier discovery in high dimensions”. In: Journal of the Royal Statistical Society Series B: Statistical Methodology 87.1 (Aug. 2024), p. 157–185. ISSN: 1467-9868. DOI: 10.1093/jrsssb/qkae084. http://dx.doi.org/10.1093/jrsssb/qkae084.

  4. N. S. Hejazi, P. Boileau, M. J. van der Laan, and A. E. Hubbard. “A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology”. In: Statistical Methods in Medical Research 32.3 (Dec. 2022), p. 539–554. ISSN: 1477-0334. DOI: 10.1177/09622802221146313. http://dx.doi.org/10.1177/09622802221146313.

  5. P. Boileau, N. S. Hejazi, M. J. van der Laan, and S. Dudoit. “Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions”. In: Journal of Computational and Graphical Statistics 32.2 (Oct. 2022), p. 601–612. ISSN: 1537-2715. DOI: 10.1080/10618600.2022.2110883. http://dx.doi.org/10.1080/10618600.2022.2110883.

  6. P. Boileau, N. T. Qi, M. J. van der Laan, S. Dudoit, and N. Leng. “A flexible approach for predictive biomarker discovery”. In: Biostatistics 24.4 (Jul. 2022), p. 1085–1105. ISSN: 1468-4357. DOI: 10.1093/biostatistics/kxac029. http://dx.doi.org/10.1093/biostatistics/kxac029.

  7. P. Boileau, N. S. Hejazi, and S. Dudoit. “Exploring high-dimensional biological data with sparse contrastive principal component analysis”. In: Bioinformatics 36.11 (Mar. 2020). Ed. by A. Mathelier, p. 3422–3430. ISSN: 1367-4811. DOI: 10.1093/bioinformatics/btaa176. http://dx.doi.org/10.1093/bioinformatics/btaa176.

Statistical Software

  1. J. Duncan, T. Tang, C. F. Elliott, P. Boileau, and B. Yu. “simChef: High-quality data science simulations in R”. In: Journal of Open Source Software 9.95 (Mar. 2024), p. 6156. ISSN: 2475-9066. DOI: 10.21105/joss.06156. http://dx.doi.org/10.21105/joss.06156.

  2. P. Boileau, N. Hejazi, B. Collica, M. van der Laan, and S. Dudoit. “cvCovEst: Cross-validated covariance matrix estimator selection and evaluation in R”. In: Journal of Open Source Software 6.63 (Jul. 2021), p. 3273. ISSN: 2475-9066. DOI: 10.21105/joss.03273. http://dx.doi.org/10.21105/joss.03273.

  3. P. Boileau, N. Hejazi, and S. Dudoit. “scPCA: A toolbox for sparse contrastive principal component analysis in R”. In: Journal of Open Source Software 5.46 (Feb. 2020), p. 2079. ISSN: 2475-9066. DOI: 10.21105/joss.02079. http://dx.doi.org/10.21105/joss.02079.

Applications

  1. L. L. Marinho, G. Lileikyte, P. Boileau, Y. Lu, M. Churpek, A. Spicer, M. Harhay, A. Luk, F. Zampieri, C. Tavares, A. Proudfoot, C. Pop, Y. Kwan, P. J. Deschenes, R. Zarychanzki, S. Lother, L. Hajjar, J. C. Jentzer, S. van Diepen, P. di Santo, R. Matthew, and P. R. Lawler. “Heterogeneity of treatment effect for milrinone versus dobutamine among patients with cardiogenic shock: A secondary analysis of the DOREMI trial”. Submitted (2026+).

  2. E. J. Elenjickal, F. Baroz, P. Boileau, M. A. Tsoukas, A. Sharma, and T. A. Mavrakanas. “The effect of canagliflozin dose on kidney and cardiovascular outcomes in type 2 diabetes and high cardiovascular risk”. Submitted (2026+).

  3. J. O. Humtsoe, H. Kim, L. Jones, J. Cevallos, P. Boileau, F. Kuo, L. G. T. Morris, and P. Ha. “Development and Characterization of MYB-NFIB Fusion Expression in Adenoid Cystic Carcinoma”. In: Cancers 14.9 (Apr. 2022), p.2263. ISSN: 2072-6694. DOI: 10.3390/cancers14092263. http://dx.doi.org/10.3390/cancers14092263.

  4. J. C. Nwanaji‐Enwerem, P. Boileau, J. M. Galazka, and A. Cardenas. “In vitro relationships of galactic cosmic radiation and epigenetic clocks in human bronchial epithelial cells”. In: Environmental and Molecular Mutagenesis 63.4 (Apr. 2022), p. 184–189. ISSN: 1098-2280. DOI: 10.1002/em.22483. http://dx.doi.org/10.1002/em.22483.

  5. A. K. Bozack, P. Boileau, A. E. Hubbard, F. C. M. Sillé, C. Ferreccio, C. M. Steinmaus, M. T. Smith, and A. Cardenas. “The impact of prenatal and early-life arsenic exposure on epigenetic age acceleration among adults in Northern Chile”. In: Environmental Epigenetics 8.1 (Jan. 2022). ISSN: 2058-5888. DOI: 10.1093/eep/dvac014. http://dx.doi.org/10.1093/eep/dvac014.

  6. A. K. Bozack, P. Boileau, L. Wei, A. E. Hubbard, F. C. M. Sillé, C. Ferreccio, J. Acevedo, L. Hou, V. Ilievski, C. M. Steinmaus, et al. “Exposure to arsenic at different life-stages and DNA methylation meta-analysis in buccal cells and leukocytes”. In: Environmental Health 20.1 (Jul. 2021). ISSN: 1476-069X. DOI: 10.1186/s12940-021-00754-7. http://dx.doi.org/10.1186/s12940-021-00754-7.