Talks and Other Events
- Teaching data science through case studies in Public Health. Joint Statistical Meeings. 2019 Jul 27-Aug 1. Denver, CO. USA.
mbkmeans: fast clustering for single cell data using mini-batch $k$-means. Bioconductor Conference. 2019 Jul 24-27. New York City, NY, USA.
- Useful Tools for Teaching And Outreach In Data Science: Workflows, Case Studies, Github Classroom, and Slack. Symposium on Data Science and Statistics. 2019. May 29-Jun 1. Bellevue, WA. USA.
- Addressing Open Challenges Data Science Education. Department of Statistics and Data Sciences, Smith College. 2019 Apr 18. Northampton, MA. USA.
- Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments. ENAR Conference. 2019 Mar 24-27. Philadelphia, PA. USA.
- Making data science accessible world-wide in the Johns Hopkins Data Science Lab. Department of Statistics, University of Connecticut. 2019 Feb 27. Storrs, CT. USA.
- Applications of Latent Variables in Identifying Systematic Errors in Genomics. Department of Statistics, Rice University. 2019 Feb 11. Houston, TX. USA.
- National Human Genome Research Institute’s Genome to Phenotype Strategic Planning Meeting. 2019 Jan 22-24. Rockville, MD, USA
- Estimating cell type composition in whole blood using differentially methylated regions. Department of Statistics, Oregon State University. 2019 Jan 14. Corvallis, OR. USA.
- Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments. Joint Statistical Meetings. 2017 Jul 29-Aug 3. Baltimore, MD, USA.
- Estimating cell type composition in whole blood using differentially methylated regions. Bioconductor conference. 2017 Jul 26-28. Boston, MA, USA.
- Missing Data and Technical Variability in Single Cell RNA-Sequencing Experiments. Ascona Workshop 2017: Statistical Challenges in Single Cell Biology. 2017 Apr 30-May 5. Ascona, Switzerland.
- Setting the Stage for Reproducibility and Replicability in Science. Brandeis University. 2017 Mar 22. Waltham, MA, USA.
- On the widespread and critical impact of systemic bias and batch effects in single-cell RNA-seq data. Presented at the Boston Single-Cell Network Meeting in March 2016 (Boston, MA, USA), presented at the Joint Statistical Meetings Aug 2016 (Chicago, IL, USA), and presented at the Single-Cell Genomics Conference Sept 2016 (Hinxton, UK).
- Batch effects and technical biases in scRNA-Seq data. HSCI Single-Cell Workshop. 2016 Nov 29-30. Harvard Medical School, Boston, MA, USA.
- Transforming the Classroom to Teach Statistics and Data Science with Active Learning. Women in Statistics and Data Science Conference. 2016 Oct 20-22. Charlotte, NC, USA.
- Towards progress in batch effects and biases in single-cell RNA-seq data. 2016 Sept 14-16. Wellcome Genome Campus, Hinxton, Cambridge, UK.
- On the widespread and critical impact of systemic bias and batch effects in single-cell RNA-seq data. Joint Statistical Meetings. 2016 Jul 31-Aug 4. Chicago, IL, USA.
- On the widespread and critical impact of systemic bias and batch effects in single-cell RNA-seq data. Boston Single-Cell Network Meeting. 2016 Mar 15. Boston, MA, USA.
- Normalization of DNA methylation and Gene Expression Data in the Context of Global Variation. Bioinformatics Meeting, Division of Immunology, Harvard Medical School. 2014 Sept 18. Boston, MA, USA.
- quantro: When should you use quantile normalization?. Flashlight talk at the Bioconductor Conference. 2014 Jul 30-Aug 1. Boston, MA, USA.
- ROpenSci Unconference. Invited to work with over 40 R enthusiasts from industry, academia, non-profits and government on projects supporting open data, open science and data visualization in R. Contributed to R-packages including explainr and catsplainr.
- Modeling Discovery Of Functional SNPs From Genome Scale Data. JSM 2011. Miami, FL, USA.
- Prediction of Missense Mutation Functionality Depends on both the Algorithm and Sequence Alignment Employed. Human Genome Variation Society’s Exploring the Functional Consequences of Genomic Variation Meeting. Washington, D.C., USA.