Final Project 1: proposal

Author
Affiliations

Jelmer Poelstra

CFAES Bioinformatics Core, Ohio State University

Dept. of Plant Pathology, Ohio State University

Deadline

November 15, 2026

Page last modified

October 17, 2026

Overview

In this first Final Project checkpoint, you will submit a summary of what you plan to do for your Final Project. We’re calling this a “proposal”, because we’ll discuss it with each of you in brief meetings the week after the deadline, to give you some feedback and guidance before you start working on the project in earnest. We will share a booking link for these meetings, similar to what we did for graded assignments.

We’re quite flexible about what your project will be, so we expect that for most of you, whatever topic you pick will be acceptable. However, if you are really unsure about your project idea, it’s a good idea to check with us before you start working on this proposal.

Directions and grading

Submission expectations

  • Deadline: Sunday Nov 15th at 11:59 pm.
  • Submission: Submit your assignment by tagging @kstarr791 and @jelmerp in a new Issue in your GitHub repo.

Academic integrity

Use of generative AI Tools is permitted.
Open-book research for the assignment is permitted.
Getting help on the assignment is not permitted, except from the instructors.
Collaborating, or completing the assignment with others, is not permitted.
Copying or reusing previous work is not permitted, except as described on the general info page.
APA Citations and/or formatting for this assignment are not required.

Rubric

You can earn a total of 10 points: 2 points for each of the 4 proposal items below (items 3–6), and 2 points for the oral discussion of your proposal with us.

For each proposal item, for full points, we’d like to see some level of detail and thoughtfulness in your answers. It doesn’t matter if you’re still uncertain about many aspects of your project, but it should be clear that you have thought seriously about the project.

While you’re allowed to use genAI tools to help you with your proposal, we expect that the proposal is largely written by yourself. In the oral discussion, we will ask you to briefly explain your plans, and check that you understand what you’ve written down. If you’re completely unable to explain parts of your own proposal, points may also be deducted from the 8 points for the written component.

Detailed steps

Setting up

  1. Create a directory /fs/ess/PAS3493/people/$USER/FP for your project, initialize a Git repository there, and create a README.md with a one-line description of your project. This will be a directory and repository that you will continue throughout the Final Project, and won’t just be for this proposal.

  2. Write your proposal in a file doc/proposal.md.

ImportantWhere to keep your data

At the end of the course, we will try to rerun your project, so we need to be able to access your raw data at OSC — and we only have access to files within the PAS3493 project. Therefore, keep your raw data (or a copy of it) inside your FP directory, for example in data/, which you’ll exclude from Git with a .gitignore file.

If your dataset is large (say, more than ~50 GB) or some steps would take more than a few hours to run, talk to us — using a subset of your data is often a good solution.

The proposal

  1. Start with a general description of what your project will be about. Describe what data you will work with and what kind of output your project will produce. If you know, be specific about the data: what type of data it is (e.g., paired-end Illumina RNA-seq reads), how many samples or files there are, their approximate total size, and where they come from. Do you already have access to the data, or are they already at OSC? For public data, include an accession number or link.

  2. Summarize how you envision the more technical aspects: include a rough, numbered list of the steps in your workflow (e.g., “1. Read QC with FastQC; 2. Read trimming with TrimGalore; …”). For each step, you can mention which program you plan to use, and whether you’ll run it with a shell script (as a Slurm batch job) or in R/Quarto. You can also mention how you will structure your directories and results. If you plan to run an nf-core pipeline, that’s fine: you would run it with a shell script that you submit as a batch job (as in week 11). But since the pipeline does much of the work for you, also plan to write a few shell scripts of your own (for example, for a step the pipeline doesn’t cover) and/or a more substantial R/Quarto analysis of the pipeline’s outputs. On the other hand, the R/Quarto part of most projects can be modest: for example, a single Quarto document that reads the output of your shell scripts and produces a few tables and figures.

  3. Describe which aspects of your project you are still uncertain about, for instance because you intend to include some topics that we have yet to cover in the course, or because you’re not sure how far you will get. Also check the list of graded aspects on the page with general information about the project, and the more detailed grading rubric on the page about your project’s final submission. If you are not sure you will be able to fulfill one of these aspects, or intend to skip something, mention that too.

  4. Describe why you chose this project. For example, because it will be useful for your research, or because it gives you practice with coding topics that you want to improve on.

Submitting your proposal

  1. Commit your proposal and README, and create a new, empty repository for your project on GitHub. Make it public, unless you are working with unpublished data that you or your lab prefer not to share yet: in that case, make it private and add kstarr791 and jelmerp as collaborators (on GitHub, go to “Settings” > “Collaborators”). Then, push your local repo to GitHub, and tag Kelsey (@kstarr791) and Jelmer (@jelmerp) in a new Issue in your repo.
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