Lukas M Weber, PhD
Assistant Professor, Biostatistics - Boston University School of Public Health
Biography
Dr. Lukas M. Weber is an Assistant Professor in the Department of Biostatistics, School of Public Health, at Boston University.
His research is in statistical genomics and biomedical data science on the development of statistical and computational methods, open-source software, and collaborative analyses for data from high-throughput genomic technologies, primarily applied to biological questions in neuroscience and cancer biology. Currently, his research is focused on data from spatial transcriptomics and single-cell platforms.
He has implemented methods and other analysis tools in a number of R software packages, and supports principles of open and reproducible science, including the development of open-source software, reproducibility of analyses, benchmarking against existing and baseline methods, providing accessible code and data resources, and publication of preprints. He has instructed several workshops on R programming and computational skills.
His training includes a postdoctoral fellowship in the Department of Biostatistics at Johns Hopkins University, a PhD in Biostatistics at the University of Zurich, Switzerland, and a MSc in Statistics at ETH Zurich, Switzerland.
Education
- University of Zurich, PhD Field of Study: Biostatistics
Websites
Publications
- Published on 1/24/2024
Weber LM, Divecha HR, Tran MN, Kwon SH, Spangler A, Montgomery KD, Tippani M, Bharadwaj R, Kleinman JE, Page SC, Hyde TM, Collado-Torres L, Maynard KR, Martinowich K, Hicks SC. The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics. Elife. 2024 Jan 24; 12. PMID: 38266073.
Read At: PubMed
- Published on 11/13/2023
Tippani M, Divecha HR, Catallini JL, Kwon SH, Weber LM, Spangler A, Jaffe AE, Hyde TM, Kleinman JE, Hicks SC, Martinowich K, Collado-Torres L, Page SC, Maynard KR. VistoSeg: Processing utilities for high-resolution images for spatially resolved transcriptomics data. Biol Imaging. 2023; 3:e23. PMID: 38510173.
Read At: PubMed
- Published on 10/20/2023
Hippen AA, Omran DK, Weber LM, Jung E, Drapkin R, Doherty JA, Hicks SC, Greene CS. Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors. Genome Biol. 2023 Oct 20; 24(1):239. PMID: 37864274.
Read At: PubMed
- Published on 7/10/2023
Weber LM, Saha A, Datta A, Hansen KD, Hicks SC. nnSVG for the scalable identification of spatially variable genes using nearest-neighbor Gaussian processes. Nat Commun. 2023 Jul 10; 14(1):4059. PMID: 37429865.
Read At: PubMed
- Published on 1/1/2023
Tippani M., Divecha H.R., Catallini II J.L., Kwon S.H., Weber L.M., Spangler A., Jaffe A.E., Hyde T.M., Kleinman J.E., Hicks S.C., Martinowich K., Collado-Torres L., Page S.C., Maynard K.R. VistoSeg: Processing utilities for high-resolution images for spatially resolved transcriptomics data. Biological Imaging. 2023; 3(e23).
- Published on 1/1/2023
Tiberi S., Crowell H.L., Samartsidis P., Weber L.M., Robinson M.D. distinct: a novel approach to differential distribution analyses. Annals of Applied Statistics. 2023; 17(2):1681-1700.
- Published on 1/1/2023
Weber L.M., Divecha H.R., Tran M.N., Kwon S.H., Spangler A., Montgomery K.D., Tippani M., Bharadwaj R., Kleinman J.E., Page S.C., Hyde T.M., Collado-Torres L., Maynard K.R., Martinowich K., Hicks S.C. The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics. eLife (accepted / in press). 2023.
- Published on 1/1/2023
Hippen A.A., Davidson N.R., Barnard M.E., Weber L.M., Gertz J., Doherty J.A., Hicks S.C., Greene C.S. Deconvolution reveals compositional differences in high-grade serous ovarian cancer subtypes. bioRxiv (preprint). 2023.
- Published on 6/10/2022
Pardo B, Spangler A, Weber LM, Page SC, Hicks SC, Jaffe AE, Martinowich K, Maynard KR, Collado-Torres L. spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data. BMC Genomics. 2022 Jun 10; 23(1):434. PMID: 35689177.
Read At: PubMed
- Published on 5/26/2022
Righelli D, Weber LM, Crowell HL, Pardo B, Collado-Torres L, Ghazanfar S, Lun ATL, Hicks SC, Risso D. SpatialExperiment: infrastructure for spatially-resolved transcriptomics data in R using Bioconductor. Bioinformatics. 2022 May 26; 38(11):3128-3131. PMID: 35482478.
Read At: PubMed
View 5 more publications:View Full Profile at BUMC
News & In the Media
- Published on August 31, 2023