Rachel Griffard-Smith

Contact

rachelgriffard@gmail.com

Summary

To harness the power of computer science, statistics, and data science and contribute to the world of bioinformatics.

Experience

University of Kansas Medical Center - Bioinformatician I

June 2024 to Present

• Actively engaged in web creative design and development.
• Designing project & planning

University of Kansas Medical Center - Graduate Research Assistant

August 2022 to May 2024

• Actively engaged in web creative design and development.
• Designing project & planning
• Working on designing

Education

School	Degree	Years attended	Cumulative GPA
University of Kansas Medical Center	M.S. Health Data Science	2022 - 2024	4.0
Uniiversity of Kansas	B.S. Behavioral Neuroscience	2017 - 2020	3.9

Publications & Projects

Therapeutic Potential of NRF2 activating drug RTA-408 in suppressing T-cell effector responses and inflammatory bowel disease

• Co-authors: Dasgupta, D., Tripathi, A., Yellapu, N.K., Pyaram, K.
• Preprocess and analyze bulk RNA-sequencing data
• Submitted to Cell Reports

Fixed single-cell RNA sequencing analysis of mouse models of asthma

• Co-authors: Sundar, I., Prasad, C.
• Preprocess and analyze fixed single-cell RNA sequencing analysis with cell ranger and Seurat

micRoclean: Decontamination for low-biomass metagenomic data

• Co-authors: Pei, D.
• micRoclean repository
• R package that contains two pipelines aimed at decontaminating low-biomass microbiome data

Plasma microbiota as novel biomarkers of early epithelial ovarian cancer detection

• Co-authors: Mahoney, D., Pei, D., Chalise, P.
• Develop pipeline to identify and remove contaminants from low-biomass blood plasma 16S rRNA sequencing microbiome data

Extracellular vesicle miRNAs as biomarkers of asthma severity

• Co-authors: Prasad, C., Pei, D., Dhillon, N., Castro, M., Sundar, I.
• Develop pipeline to preprocess and analyze small RNA data from human and mice samples
• Run correlation analysis of covariates with significantly differentially expressed miRNA from human samples

optima: an open-source R package for the Tapestri platform for integrative single cell multiomics data analysis

• Co-authors: Pei, D., Kumar Yellapu, N., Nissen, E., Koestler, D.
• optima repository
• This project is published in Bioinformatics and can be found here

Identifying differentially methylated regions in RRBS data using tiling window analysis

• Co-authors: Abbot, E., Rajendra, G., Woolbright, B., Krise, J., Thompson, J., Barchowsky, A., Hageman, M, Pei, D., Sardiu, M., Dennis, K., Taylor III, J. A.
• Identified differentially methylated regions in reduced representation bisulfite sequencing data and annotated genome using Bioconductor packages methylKit and genomation

Professional Training

Single Cell RNA-seq Workshop

National Center for Genome Resources/New Mexico-INBRE, November 2023

• Apply and expand UNIX and R knowledge for processing and analyzing single-cell RNA-seq data
• Work hands-on with tools such as SingleCellExperiment and Seraut within UNIX environment
• Collaborate with other attendees and improve communication of insights gained from single-cell RNA-seq data

Epic Cosmos Data Model Certification

Epic, June 2023

• Certified for Cosmos deidentified dataset
• Improved knowledge on how to query and manage massive datasets

IBM Data Science Professional Certificate

Coursera, 2022

SQL for Data Science with R

edX, 2021 to 2022

Skills

• Programming -
  • R
  • Unix shell-scripting
  • SQL
  • Python
  • Markdown
• Bioinformatics -
• Create and maintain pipelines for preprocessing, analysis, and visualization of ‘omic data
• Single-cell and bulk RNA sequencing analysis
• Differential expression analysis
• Leverage data from publicly available databases for analysis such as GEO and NCBI
• Statistics -

Hobbies

• Lifting
• Rock climbing
• Yoga
• Calligraphy