Learner Profiles

Learner Profile 1: Graduate Student in Molecular Biology

Name: Emily Thompson

Background: Emily is a first-year Ph.D. student in Molecular Biology at a research university. She has a strong background in basic molecular biology techniques, such as PCR, cloning, and gene expression analysis (although not bulk RNA-Seq). She completed an undergraduate-level statistics course a couple of years ago and recently completed an Introduction to R workshop, gaining basic R programming skills, but lacks experience in RNA-Seq data analysis.

Objective: Emily’s research project focuses on characterizing gene expression changes in response to specific environmental stressors in a model organism. She is interested in attending the RNA-Seq Analysis with Bioconductor workshop to learn how to analyze RNA-Seq data using R and Bioconductor, and identify differentially expressed genes that could be potential targets for future functional studies.

Current Skills:

  • Strong molecular biology background
  • Basic R programming skills from an Introduction to R course
  • Familiarity with basic statistical analysis

Desired Skills:

  • Awareness of the basic steps in RNA-Seq data analysis and which tools can be used to do them.
  • Ability to identify and interpret differentially expressed genes
  • Familiarity with visualization techniques for high-throughput data

Learner Profile 2: Bioinformatics Analyst in Biotech

Name: Alex Gomez

Background: Alex a bioinformatics analyst with two years of experience at a biotechnology company. He has a solid foundation in programming (Python, R, and SQL) and is experienced in analyzing various types of -omics data, including proteomics and genomics. He knows generally about RNA-Seq data but has never tried analyzing any.

Objective: As his company is starting to incorporate RNA-Seq into their research projects, Alex wants to attend the RNA-Seq Analysis with Bioconductor workshop to gain expertise in this area and be able to independently analyze and interpret RNA-Seq datasets.

Current Skills:

  • Strong programming skills in Python, R, and SQL
  • Experience in analyzing proteomics and genomics data
  • Familiarity with data visualization and statistical analysis

Desired Skills:

  • Proficiency in RNA-Seq data processing, normalization, and analysis
  • Understanding of the statistical methods used in differential gene expression analysis
  • Understanding of gene ontology and pathway analysis

Learner Profile 3: Post-doc in Plant Sciences

Name: Zhao Liu

Background: Zhao is a post doc in Plant Biology specializing in genetics. He has been using R and RStudio since the beginning of his PhD for eQTL analyses using R packages from CRAN but has not used many Bioconductor packages before. He has completed his first RNA-Seq experiment and attempted to analyze the data using online tutorials but is unsure if he has done it correctly because the results do not look like the tutorial practice data results.

Objective: Zhao is interested in taking an in-person workshop on RNA-seq analysis with Bioconductor to gain a better understanding of the general steps involved in analyzing RNA-seq data, have the opportunity to ask questions and receive feedback, and collaborate and interact with peers and instructors. He also hopes he might be able to ask the instructors about his specific results during the breaks.

Current Skills:

  • Strong background in plant genetics
  • Experience in using R packages to analyse biological data
  • Already attempted one RNA-Seq analysis

Desired Skills:

  • Deeper understanding of the steps in RNA-Seq analysis
  • Confidence in assessing non-typical results
  • Ability to make “biological sense” of the results.