Lukas M. Weber, PhD
Assistant Professor
Boston University School of Public Health
Biostatistics

PhD, University of Zurich



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.


Unsupervised Statistical Methods for Data-driven Analyses in Spatially Resolved Transcriptomics Data
01/01/2024 - 12/31/2026 (PI)
NIH/National Human Genome Research Institute
4R00HG012229-03



Title


Yr Title Project-Sub Proj Pubs

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

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  1. 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; PMCID: PMC10945708; DOI: 10.7554/eLife.84628;
     
  2. 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; PMCID: PMC10951916; DOI: 10.1017/S2633903X23000235;
     
  3. 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; PMCID: PMC10588129; DOI: 10.1186/s13059-023-03077-7;
     
  4. 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; PMCID: PMC10333391; DOI: 10.1038/s41467-023-39748-z;
     
  5. 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).
  6. 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.
  7. 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.
  8. 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.
  9. 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; PMCID: PMC9188087; DOI: 10.1186/s12864-022-08601-w;
     
  10. 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; PMCID: PMC9154247; DOI: 10.1093/bioinformatics/btac299;
     
Showing 10 of 15 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 15 publications over 5 distinct years, with a maximum of 7 publications in 2023

YearPublications
20191
20214
20222
20237
20241


2022 NIH NHGRI: K99/R00 Pathway to Independence Award
2021 Early Career Research Symbiont Award
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