Publications

Theory, Methodology, and Software Articles

• Tan, Y.*, Markatou, M.†, Chakraborty, S†. (2025). Flexible Empirical Bayesian Approaches to Pharmacovigilance for Simultaneous Signal Detection and Signal Strength Estimation in Spontaneous Reporting Systems Data. Statistics in Medicine. To appear. doi: 10.1002/sim.70195.

• Chakraborty, S., Guan, Z., Kostrzewa, C.E., Shen, R., and Begg, C.B. (2024). Identifying Somatic Fingerprints of Cancers Defined by Germline and Environmental Risk Factors. Genet Epidemiol. 2024 Apr 30. doi: 10.1002/gepi.22565. EPUB ahead of print. PMID: 38686586.

• Chakraborty, S., Guan, Z., Begg, C.B., and Shen, R. (2024). ‘Topical hidden genome’: a Bayesian multilevel context and topic model for genome-driven cancer-type characterization problems. Biometrics, 80(2), ujae030.

• Chakraborty, S. and Su, Z. (2023). A comprehensive Bayesian framework for envelope models. Journal of the American Statistical Association, Theory & Methods. 1-11.

• Shen Y, Park Y, Chakraborty S, Zhang C. (2023). Bayesian simultaneous partial envelope model with application to an imaging genetics analysis. New England Journal of Statistics in Data Science. 1(2):237-–269 (2023).

• Mukherjee S, Khare K, and Chakraborty S. (2023). Convergence properties of data augmentation algorithms for high-dimensional robit regression. Electronic Journal of Statistics. 17(1):19-69(2023).

• Chakraborty, S., Markatou, M., and Ball, R. (2023). Likelihood Ratio Test Based Drug Safety Assessment using R package pvLRT. R Journal, 15(1).

• Chakraborty, S., Liu, A., Ball, R., and Markatou, M. (2022). On the Use of the Likelihood Ratio Test Methodology in Pharmacovigilance. Statistics in Medicine. 1(27), pp.5395-5420.

• Lee, M., Chakraborty, S., and Su, Z. (2022). A Bayesian approach to envelope quantile regression. Statistica Sinica. 32, 1-19

• Chakraborty, S. and Wong, S. W. (2022). On the circular correlation coefficients for bivariate von Mises distributions on a torus. Stat Papers.

• Chakraborty, S., Bhattacharya, B., and Khare, K. (2022). Estimating accuracy of the MCMC variance estimator: asymptotic normality for batch means estimators. Statistics and Probability Letters, 109337.

• Chakraborty, S., Ecker, B. L., Seier, K., Aveson, V. G., Balachandran, V. P., Drebin, J. A., D’Angelica, M. I., Kingham, T. P., Sigel, C. S., Soares, K. C., Vakiani, E., Wei, C., Chandwani, R., Gonen, M., Shen, R., Jarnagin, W. R. (2021). Genome-derived Classification Signature for Ampullary Adenocarcinoma to Improve Clinical Cancer Care. Clinical Cancer Research. (27) (21) 5891-5899.

• Chakraborty, S., Martin, A., Guan, Z., Begg, C. B., and Shen, R. (2021). Mining mutation contexts across the cancer genome to map tumor site of origin. Nature Communications. 12, 3051.

• Chakraborty, S. and Wong, S. W. (2021). BAMBI: An R package for Fitting Bivariate Angular Mixture Models. Journal of Statistical Software, 99(11), 1–69.

• Chakraborty, S., Tian, L, Tseng, Y, and Wong, S. W. (2021). Bayesian analysis of coupled cellular and nuclear trajectories for cell migration. Biometrics 1-12.

• Chakraborty, S., Begg, C. B., and Shen, R. (2020). Using the “Hidden” Genome to Improve Classification of Cancer Types. Biometrics. 2020;1–11.

• Chakraborty, S., Arora A., Begg, C. B. and Shen, R. (2019). Using Somatic Variant Richness to Mine Signals from Rare Variants in the Cancer Genome. Nature Communications 10, 5506.

• Chakraborty, S. and Khare, K. (2019). Consistent estimation of the spectrum of trace class data augmentation algorithms. Bernoulli. 25(4B), 2019, 3832–3863.

• Chakraborty, S. and Khare, K. (2017). Convergence properties of Gibbs samplers for Bayesian probit regression with proper priors, Electronic Journal of Statistics. 11, 177-210.

• Maji, A., Chakraborty, S., and Basu, A. (2017). Statistical Inference based on the Logarithmic Power Divergence. Society For Application of Statistics And Allied Sciences, 2 (1), 39–51.

Collaborative Interdisciplinary Applied Scientific Articles

• Oliveira RCG de, Khalid H, Zhang Z, Chakraborty S, Benzano D, Kruger JS, McKernan SC (2025). Visit Characteristics Associated With Pediatric Dental Appointment No-Shows in an Academic Dental Setting. International Journal of Dentistry. 2025(1):2114933.

• Zhang, H., Zheng, E., Zheng, W., Huang, C., Xi, Y., Cheng, Y., Yu, S., Chakraborty, S., Bonaccio, E., Takabe, K. and Fan, X.C. (2025). OneTouch Automated Photoacoustic and Ultrasound Imaging of Breast in Standing Pose. IEEE Transactions on Medical Imaging. PMID: 40504720. DOI: 10.1109/TMI.2025.3578929. (Online ahead of print.)

• Petrela, R.B., Chhetri, C.D., Najafi, A., Zhang, Z., Rinkoski, T.A., Wieben, E.D., Fautsch, M.P., Chakraborty, S., Millen, A.E. & Patel, S.P. (2025). Associations between measures of oestrogen exposure and severity of Fuchs endothelial corneal dystrophy. BMJ Open Ophthalmology, 10(1), p.e001884. doi: 10.1136/bmjophth-2024-001884.

• Kutscher, H.L., Tamblin, M., Karki, S., Chaves, L., Baird, M., Parvin, A., Smith, E., Dube, A., Zhang, Z., Chakraborty, S., Kenney, P., and Raynolds, J.L. (2024). Inhalational Delivery of β‐glucan‐chitosan‐poly (lactic co‐glycolic) acid Nanoparticles Enhance Alveolar Macrophage Rifampin Concentrations for the Treatment of Tuberculosis. Advanced Therapeutics, p.2400057.

• Penman, S.L., Roeder, N.M., Wang, J., Richardson, B.J., Freeman-Striegel, L., Krayevsky, A., Eiden, R.D., Chakraborty, S., and Thanos, P.K., (2024). Vaporized Δ9-tetrahydrocannabinol exposure in utero has negative effects on attention in a dose-and sex-dependent manner. Pharmacology Biochemistry and Behavior, 173808.

• Penman, S.L., Roeder, N.M., Wang, J., Richardson, B.J., Pareek, O., Freeman-Striegel, L., Mohr, P., Khan, A., Eiden, R.D., Chakraborty, S., and Thanos, P.K. (2024). Vaporized nicotine in utero results in reduced birthweight, increased locomotion, and decreased voluntary exercise, dependent on sex and diet in offspring. Psychopharmacology, 1-26.

• Wang TC, Dollahon CR, Mishra S, Patel H, Abolghasemzade S, Singh I, Thomazy V, Rosen DG, Sandulache VC, Chakraborty S, Lele, Tanmay. Extreme wrinkling of the nuclear lamina is a morphological marker of cancer (2024). NPJ Precision Oncology. 8(1):1–12.

• Rosi-Schumacher, M., DiNardo, L. A., Reese, A. D., Gupta, S., Nagy, R. E., Chakraborty, S., and Carr, M. M. (2024). Comparison of Surgical Techniques for the Treatment of Congenital Nasal Pyriform Aperture Stenosis: A Systematic Review. Annals of Otology, Rhinology & Laryngology, 00034894241242179.

• Roeder, N M; Penman, S L; Richardson, B J; Wang, J; Freeman-Striegel, L; Khan, A; Pareek, O; Weiss, M; Mohr, P; Eiden, R D; Chakraborty, S; Thanos, P K. (2024). Vaporized ∆9-THC in utero results in reduced birthweight, increased locomotion, and altered wake-cycle activity dependent on dose, sex, and diet in the offspring. Life Sciences: 122447. doi: 10.1109/TUFFC.2023.3283139.

• Huang, C; Cheng, Y; Zheng, W; Bing, R; Zhang, H; Komornichi, I; Harris, L; Arany, P; **Chakraborty, S; **Zhou, Q; Xu, W; Xia, J. (2023). Dual-scan photoacoustic tomography for the imaging of vascular structure on foot. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 70(12), 1703-1713..

• Atanasova, K, Chakraborty, S (co-first author), Ratnayake, R, Khare, K, Luesch, H. (2022). An epigenetic small molecule screen to target abnormal nuclear morphology in human cells. To appear in Molecular Biology of the Cell. Molecular Biology of the Cell, 33(6), ar45.

• Batra, A, Barnard, A, Lott, D J, Willcocks, R, Forbes, S C, Chakraborty, S, Daniels, M, Arbogast, J, Triplett, W, Henricson, E, Dayan, J G, Schmalfuss, C, Sweeney, L, Byrne, B J, McDonald, C, Vandenborne, K, Walter, G A. (2022). Longitudinal changes in cardiac function in Duchenne muscular dystrophy population as measured by magnetic resonance imaging. BMC Cardiovascular Disorders, 22(1), 260.

• Ambruster, C.E., Brauer, A.L., Humby, M.S., Shao, J., Chakraborty, S. (2021). Prospective assessment of catheter-associated bacteriuria in nursing home residents: clinical presentation, epidemiology, and colonization dynamics. JCI Insight. Oct 8;6(19):e144775.

• Cassidy, D. J., Chakraborty, S., Panda, N., McKinley, S. K., Mansur, A., Hamdi I., Mullen, J., Petrusa, E., Phitayakorn, R., and Gee, D. (2020). The Surgical Knowledge “Growth Curve”: Predicting ABSITE Scores and Identifying “At-Risk” Residents. Journal of Surgical Education.

• Barnard, A. M., Wilcox, R., Forbes, S.C., Daniels, M. J., Chakraborty, S., Lott, D., J., Senesac, C. R., Arora, H., Sweeny, L., Walter, G. H., and Vandenborne, K. H. E. (2020). MR biomarkers predict clinical function in Duchenne muscular dystrophy. Neurology, 94(9), e897-e909.

• Rooney, W. D., Berlow, Y. A., Triplett, W. T., Forbes, S. C., Willcocks, R. J., Wang, D, Arora, H, Senesac, C, Lott, D. J., Finkel, R., Russman, B. S., Finanger, E. L., Chakraborty, S., O’Brien, E, Moloney, B, Barnard, A, Sweeney, H. L., Daniels, M. J., Walter, G. A., and Vandenborne, K. (2020). Modeling disease trajectory in Duchenne muscular dystrophy. Neurology, 94(15), e1622-e1633.

• Vaziri, S., Awan, O., Porche, K., Scott, K., Sacks, P., Dru, A. B., Chakraborty, S., Khare, K., Hoh, B., and Rahman, M. (2019). Reimbursement Patterns for Neurosurgery: Analysis of the NERVES Survey Results from 2011-2016. Clinical Neurology and Neurosurgery, p.105406.

• Chatterjee, N., Nair, P.K.R., Chakraborty, S., and Nair, V.D. (2018). Changes in soil carbon stocks across the Forest-Agroforest-Agriculture/Pasture continuum in various agroecological regions: A meta-analysis. Agriculture, Ecosystems and Environment, 266, 55-67.

• Vaziri, S., Wilson, J., Abbatematteo, J., Kubilis, P., Chakraborty, S., Kshitij, K., and Hoh, D. J. (2017). Predictive performance of the American College of Surgeons universal risk calculator in neurosurgical patients. Journal of Neurosurgery, 1-6.

Book Chapter

• Chakraborty, S. Genome-driven cancer site characterization: an overview of the hidden genome model. (2024). Modern inference based on health-related markers Biomarkers and Statistical Decision Making. Elsevier Inc. Editors: Vexler, A.; Yu, J.

Submitted/In-revision Scholarly Articles

• Hua, S.*, Guan, Z., Chakraborty, S†. Inferring cancer-type-specific latent mutation signatures using a Bayesian tree-based supervised topic model.

• Huang, X.*, Chakraborty, S†. A Nonparametric Bayesian Local-Global Model for Enhanced Adverse Event Signal Detection in Spontaneous Reporting System Data. arXiv.

• Wang, S., Chakraborty, S., Qin, Q., Bai, R. Neural-g: A Deep Learning Framework for Mixing Density Estimation.

• Chakraborty, S., Khare, K, Michailidis, G. arXiv.

• Liu, A., Markatou, M., Chakraborty, S., and Ball, R. A pattern discovery algorithm for pharmacovigilance signal detection.

• Roeder, N.M., Penman, S.L., Richardson, B.J., Wang, J., Freeman-Striegel, L., Pareek, O., Eiden, R., Chakraborty, S., Thanos, P. Nicotine e-cigarette exposure in utero diminishes spatial memory and has negative effects on attention in a dose-, diet- and sex-dependent manner.

• Tan, Y.*, Markatou, M., Chakraborty, S†. pvEBayes: An R Package for Empirical Bayes Methods in Pharmacovigilance.

  ${}^*$: Ph.D. Advisee; †: Senior authorship

Statistical Software Development

• BAMBI: An R package for Bivariate Angular Mixture Models. Downloaded over 40,000 times.
• variantprobs: An R package for estimating probabilities and expected numbers of mutations in the tumor genome.
• hidgenclassifier: An R package implementing Key functions for Bayesian hidden genome classifiers. Includes functions for preprocessing genomic data, fitting and predicting from hidden genome classifiers.
• pvLRT: An R package for likelihood ratio test based methods for pharmacovigilance.
• pvEBayes: Empirical Bayes Methods for Pharmacovigilance