Career Overview

(2021 - Current) I’ve been working to build open source resources to empower cancer researchers primarily through software and education Afiaz et al. (2024).

(2018 - 2021) At the Childhood Cancer Data Lab, I helped equip childhood cancer researchers to use data science to empower their research (Dang et al. 2020, 2021; J. Shapiro et al. 2021; J. A. Shapiro et al. 2023).

(2015 - 2018) In grad school, I worked on DNA methylation data in Parkinson’s disease (Kochmanski, Savonen, and Bernstein 2019).

(2013 - 2015) I started out in neuroscience studying the transcriptomics of drug addiction (Bannon, Savonen, Hartley, et al. 2015; Bannon, Savonen, Jia, et al. 2015; Saad et al. 2018, 2019).

Grant Involvement Summary

  • ITCR Training Network
    • Role: Key Personnel
    • Main tasks:
      • Leading development of software tools for scalable bioinformatics education.
      • Curriculum development for reproducibility and software courses
  • Training Module for Reproducibility
    • Role: Curriculum developer
    • Main tasks: Development of online curriculum for reproducibility
  • DataTrail
    • Role: Curriculum developer
    • Main tasks:
      • Teaching data science
      • Internship creation and mentorship
      • Curriculum maintenance
  • Fred Hutch TDS-IRC Berger lab collabration
    • Role: Software engineer lead
    • Main tasks:
      • Multidiscplinary collaboration
      • Development of software packages for CRISPR paired guide screenings
  • Data Science for Environmental Health
    • Role: Curriculum developer
    • Main tasks: Assisting with reproducibility and curriculum maintenance

Past Grant Involvement

  • OpenPBTA
    • Role: Biological Data Analyst
    • Main tasks:
      • Scientific code review
      • Reproducible analyses
      • Genomic variant caller comparison analyses
  • Refine.bio
    • Role: Biological Data Analyst
    • Main tasks:
      • Internal testing of refine.bio
      • Creating reproducible genomics examples for use with refine.bio
  • CCDL Training
    • Role: Biological Data Analyst
    • Main tasks:
      • Creating reproducible genomic data curriculum
      • Teaching reproducible analyses to cancer researchers

Other involvements

Committees

Publication peer review

My colleagues and I have written about:

  • Data science teaching approaches (C. Savonen et al. 2023; Candace Savonen et al. 2023).
  • How to evaluate informatics software (Afiaz et al. 2023, 2024).
  • Using AI chatbots for science (Humphries et al. 2023).

I’ve also been a reviewer for:

  • PLOS Computational Biology
  • Journal of Statistics and Data Science Education

Full list of publications

Afiaz, Awan, Andrey A. Ivanov, John Chamberlin, David Hanauer, Candace L. Savonen, Mary J. Goldman, Martin Morgan, et al. 2024. “Best Practices to Evaluate the Impact of Biomedical Research Software-Metric Collection Beyond Citations.” Bioinformatics (Oxford, England) 40 (8): btae469. https://doi.org/10.1093/bioinformatics/btae469.
Afiaz, Awan, Andrey Ivanov, John Chamberlin, David Hanauer, Candace Savonen, Mary J Goldman, Martin Morgan, et al. 2023. “Evaluation of Software Impact Designed for Biomedical Research: Are We Measuring What’s Meaningful?” https://arxiv.org/abs/2306.03255.
Bannon, Michael J., Candace L. Savonen, Zachary J. Hartley, Magen M. Johnson, and Carl J. Schmidt. 2015. “Investigating the Potential Influence of Cause of Death and Cocaine Levels on the Differential Expression of Genes Associated with Cocaine Abuse.” Edited by Z. Carl Lin. PLOS ONE 10 (2): e0117580. https://doi.org/10.1371/journal.pone.0117580.
Bannon, Michael J., Candace L. Savonen, Hui Jia, Fabien Dachet, Steven D. Halter, Carl J. Schmidt, Leonard Lipovich, and Gregory Kapatos. 2015. “Identification of Long Noncoding RNAs Dysregulated in the Midbrain of Human Cocaine Abusers.” Journal of Neurochemistry 135 (1): 50–59. https://doi.org/10.1111/jnc.13255.
Dang, Mai T., Michael V. Gonzalez, Krutika S. Gaonkar, Komal S. Rathi, Patricia Young, Sherjeel Arif, Li Zhai, et al. 2021. “Macrophages in SHH Subgroup Medulloblastoma Display Dynamic Heterogeneity That Varies with Treatment Modality.” Cell Reports 34 (13): 108917. https://doi.org/10.1016/j.celrep.2021.108917.
Dang, Mai T., Michael Gonzalez, Krutika S. Gaonkar, Komal S. Rathi, Patricia Young, Sherjeel Arif, Li Zhai, et al. 2020. “Single-Cell Transcriptomic Profile Reveals Macrophage Heterogeneity in Medulloblastoma and Their Treatment-Dependent Recruitment,” February. https://doi.org/10.1101/2020.02.12.945642.
Humphries, Elizabeth M., Carrie Wright, Ava M. Hoffman, Candace Savonen, and Jeffrey T. Leek. 2023. “What’s the Best Chatbot for Me? Researchers Put LLMs Through Their Paces.” Nature, September. https://doi.org/10.1038/d41586-023-03023-4.
Kochmanski, Joseph, Candace Savonen, and Alison I. Bernstein. 2019. “A Novel Application of Mixed Effects Models for Reconciling Base-Pair Resolution 5-Methylcytosine and 5-Hydroxymethylcytosine Data in Neuroepigenetics.” Frontiers in Genetics 10 (September). https://doi.org/10.3389/fgene.2019.00801.
Saad, Manal H., Matthew Rumschlag, Michael H. Guerra, Candace L. Savonen, Alaina M. Jaster, Philip D. Olson, Adnan Alazizi, et al. 2019. “Differentially Expressed Gene Networks, Biomarkers, Long Noncoding RNAs, and Shared Responses with Cocaine Identified in the Midbrains of Human Opioid Abusers.” Scientific Reports 9 (1). https://doi.org/10.1038/s41598-018-38209-8.
Saad, Manal H., Candace L. Savonen, Matthew Rumschlag, Sokol V. Todi, Carl J. Schmidt, and Michael J. Bannon. 2018. “Opioid Deaths: Trends, Biomarkers, and Potential Drug Interactions Revealed by Decision Tree Analyses.” Frontiers in Neuroscience 12 (October). https://doi.org/10.3389/fnins.2018.00728.
Savonen, Candace, Carrie Wright, Ava M. Hoffman, Elizabeth M. Humphries, Katherine E. L. Cox, Frederick J. Tan, and Jeffrey T. Leek. 2023. “Motivation, Inclusivity, and Realism Should Drive Data Science Education.” https://arxiv.org/abs/2305.06213.
Savonen, Candace, Carrie Wright, Ava M. Hoffman, John Muschelli, Katherine Cox, Frederick J. Tan, and Jeffrey T. Leek. 2022a. “Open-Source Tools for Training Resources – OTTR.” https://arxiv.org/abs/2203.07083.
———. 2022b. “Open-Source Tools for Training Resources OTTR.” Journal of Statistics and Data Science Education, October, 1–12. https://doi.org/10.1080/26939169.2022.2118646.
Savonen, C, C Wright, A Hoffman, E Humphries, K Cox, F Tan, and J Leek. 2023. “Motivation, Inclusivity, and Realism Should Drive Data Science Education [Version 1; Peer Review: Awaiting Peer Review].” F1000Research 12 (1240). https://doi.org/10.12688/f1000research.134655.1.
Shapiro, Joshua A., Krutika S. Gaonkar, Stephanie J. Spielman, Candace L. Savonen, Chante J. Bethell, Run Jin, Komal S. Rathi, et al. 2023. “OpenPBTA: The Open Pediatric Brain Tumor Atlas.” Cell Genomics, 100340. https://doi.org/https://doi.org/10.1016/j.xgen.2023.100340.
Shapiro, Joshua, Candace Savonen, Chante Bethell, Krutika Gaonkar, Yuankun Zhu, Miguel Brown, Nhat Duong, et al. 2021. “OMIC-14. OPENPBTA: AN OPEN PEDIATRIC BRAIN TUMOR ATLAS.” Neuro-Oncology 23 (Supplement_1): i40–40. https://doi.org/10.1093/neuonc/noab090.161.
Look on GitHub to see what I've been working on recently.
You can contact me at cansav09@gmail.com .