Interested in providing data for student projects? Fill out this form by Sept 2, 2024.

Project Scope and Expectations

Students work on projects in groups of 3-4 over the course of 4 months while balancing a heavy course load. On average, each student will dedicate ~5-10 hours per week to project work. Keep in mind that this may look different from a PhD rotation student (both in time commitment level and incoming foundational knowledge). We recommend reaching out to the program (coonrod@uoregon.edu) if concerns arise regarding project expectations. Our goal is for the project to be mutually beneficial to both students and mentors. Projects may result in publishable data, but this is not an expectation; many projects are exploratory, validation-based, or primarily involve pipeline comparisons. In the rare event that IP is generated, that IP is owned by the mentor and institution sponsoring the project.

What is expected from groups that provide projects?

• Identify a mentor to engage with students periodically (twice a month, on average) to answer questions about the project
  • It is not required for the mentor to be experienced in bioinformatics/computational biology
  • BGMP faculty provide technical mentorship, mainly computational in nature, when possible
• Provide a project description that:
  • Defines the goals of the project
  • Provides instructions for the students about how data can be accessed
  • Provides relevant papers from the field’s literature
• Project data must be available NO LATER than Sept 2, 2024. Please do not submit projects that have data “coming soon”

Learning outcomes for students

• Understand and be able to communicate (to technical and non-technical audiences):
  • Project goals and motivation
  • Broader impacts of project
• Demonstrate collaborative working skills
  • Project management
  • Communication of progress
    • To program staff and peers
    • To mentor
  • Create and execute plan for data analysis or pipeline development
• Demonstrate computational skills
  • Write original scripts, employ HPC, and utilize bioinformatics software for analyses
  • Interpret data and employ appropriate statistical tests and concepts to support conclusions about data
• Present conclusions with clear visuals through
  • talks
  • posters
  • write-ups
  • project update emails

2024 Tentative Timeline

In addition to periodic “lab meeting” style project updates, program faculty will regularly check in with groups to assess progress and group dynamics. Our goal is for student groups to make satisfactory progress throughout the term, and to meet the mentor's expectations. However, we may be limited in our ability to fully assess progress. We recommend a program faculty member participate in the first mentor/student meeting to facilitate understanding of the project goals, scope, and expectations. We also encourage mentors to communicate with program faculty if needed.

Tentative timeline for group projects:

Examples of project possibilities (not exhaustive)

• De novo transcriptome assembly and annotation
• Genome assembly
• Microbiota community analysis
• Differential gene expression analysis
• Alternative splicing profiling in human disease
• Single-cell RNA-seq
• Pipeline development/comparison
• Image analysis and automation
• Machine learning applications

Student background

During the summer term, students undergo intensive training in basic programming in Python, Unix shell (Bash), and R. Students understand how sequencing technology works, basic experimental design, and how to solve common problems in computational biology. Specifically, students are practiced in:

• Command line navigation
• Reading, evaluating, and presenting scientific literature in many Life Science disciplines
• Working on a shared computing environment (HPC) and job submission
• Parsing sequencing and other types of data
• Analyses of genomic data:
  • QC
  • genome assembly
  • differential gene expression analysis
  • visualization of multivariate data
  • phylogenetics
  • 16S amplicon-based profiling of microbial communities
• Biological statistics (foundational in the summer, "advanced" in fall and winter terms)

Publishing

The standard conventions of authorship should be followed: if student contributions are included in a publication, then authorship should be considered. 

Example Posters

Below are examples of posters that project groups have created for past Genomics in Action meetings. Click the links below to view the posters.

• Powers A, Sisson Z, Reddy V, Hosseinzadeh P. A Network Based Analysis of Host-Pathogen Interactions. Genomics in Action, 2022.
• Grove J, Koehler S, Szczepanski N, Biondi T, Hovde B. Novel Algal Pathogen Identification using Hi-C Metagenomics. Genomics in Action, 2021.
• Ostrovsky A, Rezzonico M, Richardson R, Hetrick B, McCurdy C. Lipid Profiling & RNA-sequencing of Offspring Reveal Transgenerational Consequences of Maternal Diets. Genomics in Action, 2019.
• Bubie A, Erikson C, Nassar L, Baumann P. Genome Annotation and Characterization of Parthenogenetic Aspidoscelis Lizards. Genomics in Action, 2018.
• VanCampen J, Norris B, Claridge SE, Simons ND, Ting N, Eick G, Sterner KN. De novo prediction in the Ugandan red colobus genome reveals miRNAs unique to SIV non-progressors. Genomics in Action, 2018.
• Dinwiddie D, Ho D, Zavoshy N, McGuire K. Soil microbial community structure in Lambir Hills National Park. Genomics in Action, 2018.