Student Projects

Interested in providing data for student projects? Fill out this form by Sept 3, 2021.

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 the program if concerns arise regarding project expectations. Our goal is for the project to be mutually beneficial to student and mentor. 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 provide technical mentorship, mainly computational in nature, if 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 3, 2021, 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
    • Project broader impacts
  • 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

2021 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 meet the mentor's expectations. However, we may be limited in our ability to fully access progress. We recommend a program faculty member participate in a mentor/student meeting to facilitate understanding of the project goals, scope, and expectations. We also encourage mentors to communicate with program faculty if needed.

Rough timeline for group projects:

Date Major Checkpoint Details
Sept 3, 2021 Project description submission deadline Projects will be reviewed by BGMP staff to ensure that the scope of the project is appropriate for our class and that the data are available
Sept 8, 2021 Potential topics communicated to students Projects are discussed in class
Sept 29, 2021 Assign projects to student groups Student project preferences are considered, each group has ~3 students, projects with insufficient student interest may be dropped
Oct 5 & 7, 2021 Groups present project background and motivation Mentors welcome to attend
Nov 8 & 11, 2021 Groups present project to general audience/layperson Mentors welcome to attend
Early-Dec 2021 Formal presentation of projects Final oral presentations, mentors invited
Jan/Feb 2022 Formal write-up of data/results Mentors can specify preferred format (ex: GitHub repo, poster, results section of paper, etc.)
Late-Jan, 2022 Poster presentations Poster session at Genomics in Action meeting, wrap-up of 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.