Last updated: 2018-12-13

workflowr checks: (Click a bullet for more information)
  • R Markdown file: up-to-date

    Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

  • Repository version: d9439d5

    Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

    Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
    
    Ignored files:
        Ignored:    .DS_Store
    
    Untracked files:
        Untracked:  docs/photo.jpg
    
    
    Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
Expand here to see past versions:
    File Version Author Date Message
    Rmd d9439d5 courtneyschiffman 2018-12-13 wflow_publish(c(“analysis/about.Rmd”, “analysis/publications.Rmd”,
    html d0ccc3c courtneyschiffman 2018-12-13 Build site.
    html b4fb801 courtneyschiffman 2018-12-13 Build site.
    Rmd 8886030 courtneyschiffman 2018-12-13 wflow_publish(c(“analysis/cv.Rmd”, “analysis/”))


Education

  • 2014-2019, PhD in Biostatistics, University of California, Berkeley

    • Designated emphasis in Computational and Genomic Biology
  • 2009-2013, BA in Applied Mathematics, University of California, Berkeley

Research Experience

University of California, Berkeley, School of Public Health

  • Graduate Student Researcher, NIH R33 project, Supervisors Stephen Rappaport and Sandrine Dudoit, Spring 2016-Present, Using Adductomics to Characterize Exposures to Carcinogens.

    • Development of pre-processing and statistical pipelines for the analysis of LC-MS data for adductomics and metabolomics for cancer specimens.
  • Graduate Student Researcher, Superfund Core D, Supervisor Alan Hubbard, Summer 2015-Fall 2015, Exploring the genetic effects of occupational benzene exposure.

    • Development of benzene exposure gene expression signature using machine learning

University of California, Berkeley, Statistics

  • Graduate Student Researcher, FRG Fund, Supervisor Haiyan Huang, Summer 2015, Statistical analysis of microarray data sets and single-cell RNA-Seq.

    • Development of single-cell similarity measure for clustering of single-cell data, statistical analysis of single-cell protein expression.

Teaching

  • Graduate Student Instructor, Concepts of Probability, Spring 2015.
  • Graduate Student Instructor, Concepts of Probability, Fall 2014
  • Graduate Student Instructor, Introductory Probability and Statistics, Fall 2014.

Awards

Outstanding Graduate Student Instructor Award (2014-2015).

Internships

  • Genentech Biostatistics Summer Internship 2018 Program, Advisers Nicholas Lewin-Koh and Joseph Paulson.

    • statistical analysis of microbiome data and observation of all stages of drug development

Additional relevant activities

  • Expert in R programming

  • Experience with Python and SQL

References


This reproducible R Markdown analysis was created with workflowr 1.1.1