Savonen CV 2022.docx

Savonen page

July 1st 2022

CURRICULUM VITAE

CANDACE SAVONEN, M.S.

PROFESSIONAL DATA

Business Address, Phone, & E-mail

Hutch Data Science Lab Phone: (734) 735 - 2469

Fred Hutchinson Cancer Center Email: csavonen@fredhutch.org

Professional Social Media Handles

github: cansavvy

website: cansavvy.com

twitter: cansavvy

Pronouns

She/Her

EDUCATION AND TRAINING

Degrees

M.S. / 2018 Michigan State University, Neuroscience

Advisor: Alison Bernstein Ph.D.

Thesis project: Differentially methylated gene networks in Parkinson’s disease

B.S. / 2013 Oakland University, Biology

B.A. / 2013 Oakland University, Psychology

PROFESSIONAL EXPERIENCE

Fred Hutchinson Cancer Center

Data Scientist, Hutch Data Lab, Fred Hutchinson Cancer Center (July 2022 - Current).

Johns Hopkins University

Research Associate, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, (April 2021 – June 2022).

Other Non-JHU Professional Experience

Biological Data Analyst, Childhood Cancer Data Lab – Alex’s Lemonade Stand Foundation, Philadelphia, PA (September 2018 – March 2021).

Advisor: Jaclyn N. Taroni, Ph.D.
Creating educational materials to help equip pediatric cancer researchers with the tools, skills, and pipelines needed to empower their research.

Graduate Student Researcher, Neuroscience Program, Michigan State University, East Lansing, MI (June 2015 – 2018).

Advisor: Alison Bernstein, Ph.D.
Investigating differentially methylated gene networks in Parkinson’s disease.

Research Assistant, Wayne State University School of Medicine, Detroit, MI, (May 2013 – June 2015).

Advisor: Michael J Bannon, Ph.D.
Investigating differential gene expression in postmortem human brain as it relates to drug addiction.

PUBLICATIONS

Journal Articles (peer reviewed)

Savonen, Candace, Carrie Wright, Ava M. Hoffman, John Muschelli, Katherine Cox, Frederick J. Tan, and Jeffrey T. Leek. 2022. “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.

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.

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.

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.

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.

Articles, Editorials and Other Publications Not Peer Reviewed

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.

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.

PRACTICE ACTIVITIES

Media Dissemination

Overcoming the steep data science learning curve in childhood cancer research using workshops (2019)

Blog post: https://www.ccdatalab.org/blog/7/25/19/overcoming-the-steep-data-science-learning-curve-in-childhood-cancer-research-using-workshop

Someone is wrong on the internet and it’s probably us (2020)

Blog post: https://www.ccdatalab.org/blog/2020/5/29/openpbta-someone-is-wrong-on-the-internet-and-its-probably-us

PART II

TEACHING

Educational Resources and Software Tools

Open Source Tools for Training Resources (OTTR)

Automation tools, templates and guides for online course creation

github: https://github.com/jhudsl/OTTR_Template/

ITCR Training Network courses

The ITN is a collaborative effort of researchers to catalyze informatics research through training opportunities (NCI UE5CA254170). ITN Courses are published on Leanpub and Coursera and on their own Bookdown websites.

Published ITN Courses:

Documentation and Usability

A course to cover the basics of creating documentation and tutorials to maximize the usability of informatics tools.

github: https://github.com/jhudsl/Documentation_and_Usability

Introduction to Reproducibility in Cancer Informatics

Equip learners with reproducibility skills they can apply to their existing analyses scripts and projects. This course opts for an “ease into it” approach.

github: https://github.com/jhudsl/Adv_Reproducibility_in_Cancer_Informatics

Advanced Reproducibility in Cancer Informatics

To equip learners with a deeper knowledge of the capabilities of reproducibility tools and how they can apply to their existing analyses scripts and projects.

github: https://github.com/jhudsl/Reproducibility_in_Cancer_Informatics

Choosing Genomics Tools (in progress)

To help learners find resources and tools to help them process and interpret their genomic data.

Bookdown

github: https://github.com/fhdsl/Choosing_Genomics_Tools

refinebio-examples

A self-guided tutorial to help users analyze processed gene expression data from refine.bio repository.

github: https://github.com/AlexsLemonade/refinebio-examples

Childhood Cancer Data Lab RNA-seq Workshops

A short format workshop (3 – 5 days) to introduce pediatric cancer researchers to the basics of single-cell and bulk RNA-seq data analysis.

github: https://github.com/AlexsLemonade/training-modules

Classroom Instruction – Workshops

ITCR Training Network Workshops

(February 2022) Documentation and Usability, virtual
(April 2022) Documentation and Usability, virtual
(June 2022) Documentation and Usability, virtual
(September 2022) ITCR trainee day, St Louis, MO

Childhood Cancer Data Lab single-cell and bulk RNA-seq Workshops

(March 2021) Bulk RNA-seq and pathway analyses, virtual
(August 2020) Bulk RNA-seq, virtual
(July 2020) Single-cell RNA-seq, virtual
(June 2020) Bulk RNA-seq, virtual
(May 2020) Bulk RNA-seq, virtual
(October 2019) Bulk and single-cell RNA-seq, Philadelphia, PA
(September 2019) Bulk and single-cell RNA-seq, San Francisco, CA
(June 2019) Bulk and single-cell RNA-seq, Chicago, IL
(March 2019) Bulk and single-cell RNA-seq, Houston, TX

PRESENTATIONS

Scientific Meetings

Oral Presentations

Increasing data analysis skills in the pediatric cancer community with the Childhood Cancer Data Lab training workshops

(2019) Great Lakes Bioinformatics Conference Madison, WI

Poster Presentations

Differentially methylated gene networks in Parkinson’s disease

(2018) International Society for Computational Biology Conference, Chicago, IL
(2018) Michigan Chapter of Society for Neuroscience, Detroit, MI
(2017) Society for Neuroscience, Washington, DC

Microglia are more active in schizophrenia as evidenced by gene expression signatures

(2017) Michigan Chapter of Society for Neuroscience, Ann Arbor, MI
(2016) Michigan Chapter of Society for Neuroscience, East Lansing, MI

Differential expression of lncRNAs in the ventral midbrain of cocaine abusers

(2014) Michigan Chapter of Society for Neuroscience, Kalamazoo, MI

Dopamine-cell specific expression of long non-coding RNAs in the ventral midbrain

(2014) WSU Graduate Student Research Day, Detroit, MI

ADDITIONAL INFORMATION

Personal statement

My interest is in making genomic data science tools more easily attainable to those who are looking to impactfully apply them to their areas of knowledge and expertise. I am passionate about creating educational materials which emphasize reproducibility and using scalable methods to disseminate educational materials. I have been involved in creating and delivering bioinformatic education materials for cancer genomics. My neuroscience background has helped me empathize with researchers who are looking to bridge the data science knowledge gap.

Keywords

Bioinformatics, Data Science, Data Analysis, Education, Reproducibility, Gene Expression, Genomics