My research interests focus on the development of statistical methods and open-source bioinformatic tools to analyze data from a wide range of high-throughput genomic, transcriptomic, and proteomic technologies. I am particularly interested in developing methods and software for the Bioconductor Project. One of the key purposes of the methods I develop is to identify molecular features, such as genomic coordinates, genes/transcripts, or proteins that change in accessibility, expression, or abundance, respectively, between experimental conditions. At Pitt, I collaborate with research groups from the Department of Orthopedic Surgery to understand genomic and molecular mechanisms in spine-related diseases, other orthopedic issues, and patients with traumatic brain injury. These collaborations are the foundation from which my methodological and computational ideas originate.
2020 | University of North Carolina at Chapel Hill, NC | PhD in Biostatistics
2014 | University of Campinas, Brazil | MSc in Statistics
2012 | University of Campinas, Brazil | BSc in Statistics
Baldoni PL, Chen L, Smyth GK. Faster and more accurate assessment of differential transcript expression with Gibbs sampling and edgeR v4. NAR Genom Bioinform. 2024 Nov 4;6(4):lqae151. doi: 10.1093/nargab/lqae151. PMID: 39498433; PMCID: PMC11532793.
Chen Y, Chen L, Lun AT, Baldoni PL, Smyth GK. edgeR 4.0: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets. bioRxiv. 2024:2024-01.
Baldoni PL, Chen Y, Hediyeh-Zadeh S, Liao Y, Dong X, Ritchie ME, Shi W, Smyth GK. Dividing out quantification uncertainty allows efficient assessment of differential transcript expression with edgeR. Nucleic Acids Res. 2024 Feb 9;52(3):e13. doi: 10.1093/nar/gkad1167. PMID: 38059347; PMCID: PMC10853777.
Dong X, Du MRM, Gouil Q, Tian L, Jabbari JS, Bowden R, Baldoni PL, Chen Y, Smyth GK, Amarasinghe SL, Law CW, Ritchie ME. Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures. Nat Methods. 2023 Nov;20(11):1810-1821. doi: 10.1038/s41592-023-02026-3. Epub 2023 Oct 2. PMID: 37783886.
Baldoni PL, Rashid NU, Ibrahim JG. Efficient detection and classification of epigenomic changes under multiple conditions. Biometrics. 2022 Sep;78(3):1141-1154. doi: 10.1111/biom.13477. Epub 2021 May 3. PMID: 33860525.
Baldoni PL, Sotres-Alvarez D, Lumley T, Shaw PA. On the Use of Regression Calibration in a Complex Sampling Design With Application to the Hispanic Community Health Study/Study of Latinos. Am J Epidemiol. 2021 Jul 1;190(7):1366-1376. doi: 10.1093/aje/kwab008. PMID: 33506244; PMCID: PMC8245895.
Baldoni PL, Rashid NU, Ibrahim JG. Improved detection of epigenomic marks with mixed-effects hidden Markov models. Biometrics. 2019 Dec;75(4):1401-1413. doi: 10.1111/biom.13083. Epub 2019 Oct 17. PMID: 31081192; PMCID: PMC6851437.
