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Rachel Griffard-Smith

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

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
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