Interested in providing data for student projects? Contact Leslie Coonrod and Stacey Wagner.
Project Scope and Expectations
BGMP students work on projects in groups of 3-4 over the course of 4 months while balancing additional coursework. On average, each student will dedicate ~5 hours per week to project work. Projects may result in publishable data, although many projects are exploratory, validation based, or primarily involve pipeline comparisons.
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
- Optional: mentor is experienced in bioinformatics/computational biology
- BGMP faculty will provide technical mentorship when applicable
- 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
Learning outcomes for students
- Define the biological background and explain relevance to technical and non-technical audiences
- Demonstrate collaborative working skills
- Evaluate data quality
- Create and execute plan for data analysis
- 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
2019 Tentative Timeline
In addition to periodic “lab meeting” style project updates, following is a rough timeline for the projects:
Examples of types of analyses from previous years
- De novo transcriptome assembly and annotation
- Genome assembly
- Phage display analysis to determine peptide binding specificity to a protein
- Microbiota community composition association with diet (16S amplicon)
- Identification of adapted mutations within experimentally evolved gut bacterium (whole genome sequencing)
- Differential gene expression analysis
- Alternative splicing profiling in human disease
- Single-cell RNA-seq
During the summer term, students undergo intensive training in basic programming in Python, Unix shell, and R. Students understand how sequencing technology works, 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:
- genome assembly
- transcriptome assembly
- differential gene expression analysis
- visualization of multivariate data
- 16S amplicon-based profiling of microbial communities
- Biological statistics (courses during fall and winter terms)
The standard conventions of authorship should be followed: if student contributions are written up in a publication, then authorship should be considered.
Below are examples of posters project groups have created for past Genomics in Action meetings. Click the links below to view the posters.
- 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.