scCODA is a Bayesian model for compositional single-cell data analysis
Büttner, M., Ostner, J., Müller, C. L., Theis, F. J., and Schubert, B. (2021). "scCODA is a Bayesian model for compositional single-cell data analysis" Nat. Commun. 12, 6876.
CV
Education
- B.S. in Mathematics, Technical University of Munich, 2017
- M.S. in Mathematics in Data Science, Technical University of Munich, 2020
Work experience
- 2020-2024: PhD student
- Helmholtz Munich
- LMU Munich
- Duties included:
- Development of statistical models for compositional analysis of high-throughput sequencing data
- Computational analysis of scRNA-seq and amplicon sequencing datasets
- Creation, extension and maintenance of various Python packages
- Supervision of student assistants and Master’s theses
- Responsibilities for compute cluster access as group IT representative
- Presentation of my work at international workshops and conferences
- Supervisor: Prof. Dr. Christian L. Müller
- 2019-2020: Working Student Computational Biology
- Helmholtz Munich
- Duties included:
- Productive implementation of the statistical model developed in my Master’s thesis
- Development of new functions for the scanpy package for scRNA-seq data analysis in Python
- Supervisor: Dr. Benjamin Schubert
- 2016-2017: Intern/Working Student Data Science
- metoda GmbH, Munich
- Duties included:
- Data analysis and visualization for determination of time-related correlations
- Optimization of data analysis algorithms
- Integration of external data into the company BI
- Semantic analysis of product description on Amazon
- Supervisor: Dr. Jan Heyder
Skills
- Statistics and Data analysis
- Compositional statistics
- Bayesian analysis
- Score Matching Optimization
- Synthetic data generation
- Data thinning and synthetic null testing
- Statistical testing
- Numerics
- Machine Learning
- Applications
- Single-cell RNA sequencing
- Microbiome analysis
- High-throughput sequencing
- Flow Cytometry
- Programming and Computing
- Python
- R
- SQL
- BASH
- slurm
- C
- Tensorflow
- PyTorch
- pymc3
- Docker
Publications
tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data
Ostner, J., Carcy, S., and Müller, C. L. (2021). "tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data." Front. Genet. 12, 766405.
Best practices for single-cell analysis across modalities
Heumos, L., Schaar, A. C., Lance, C., Litinetskaya, A., Drost, F., Zappia, L., et al. (2023). "Best practices for single-cell analysis across modalities". Nat. Rev. Genet., 1–23.
MetaIBS - large-scale amplicon-based meta analysis of irritable bowel syndrome
Carcy, S., Ostner, J., Tran, V., Menden, M., and Müller, C. L. (2024). "MetaIBS - large-scale amplicon-based meta analysis of irritable bowel syndrome". bioRxiv, 2024.01.22.575775. doi: 10.1101/2024.01.22.575775
BacSC: A general workflow for bacterial single-cell RNA sequencing data analysis
Ostner, J., Kirk, T., Olayo-Alarcon, R., Thöming, J., Rosenthal, A. Z., Häussler, S., et al. (2024). BacSC: A general workflow for bacterial single-cell RNA sequencing data analysis. bioRxiv. doi: 10.1101/2024.06.22.600071
Pertpy: an end-to-end framework for perturbation analysis
Heumos, L., Ji, Y., May, L., Green, T., Zhang, X., Wu, X., et al. (2024). Pertpy: an end-to-end framework for perturbation analysis. bioRxiv, 2024.08.04.606516. doi: 10.1101/2024.08.04.606516
Score matching for differential abundance testing of compositional high-throughput sequencing data
Ostner, J., Li, H., and Müller, C. L. (2024). Score matching for differential abundance testing of compositional high-throughput sequencing data. bioRxiv, 2024.12.05.627006. doi: 10.1101/2024.12.05.627006
Talks
Bayesian tree-aggregated analysis of compositional amplicon and single-cell data
Talk at DAGStat, Hamburg, Germany
Bayesian tree-aggregated analysis of compositional amplicon and single-cell data
Talk at Helmholtz Munich Microbiome Day, Munich, Germany
Flexible and efficient modeling of compositional count data from high-throughput sequencing
Poster at Probabilistic Modeling in Genomics, Cold Spring Harbor, NY, USA
Flexible and efficient modeling of compositional count data from high-throughput sequencing
Poster at LMU Statistics department retreat, Holzhausen am Ammersee, Germany
Bayesian Modeling of Compositional Changes in Microbial Abundance Data
Talk at ICSA Applied Statistics Symposium, Ann Arbor, MI, USA
Flexible and efficient modeling of compositional count data from high-throughput sequencing
Poster at ISMB/ECCB conference, Lyon, France
Voluntary work
- Member of the organization team for the StuStaCulum-Festival 2019-2024:
- Communication and project management in a team of over 100 people
- Coordination, supervision and technical support of up to 20 cashiers at a time
- Technical support for cash registers
- Bookkeeping duties
- Development and operation of a cashless payment system (StuStaPay)
- Club swimming (VfL Waldkraiburg)
- Youth Coordinator
- Certified coach in competitive swimming
- Certified judge for swimming competitions
- Life guard (DLRG)