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WiFi: carnegie / ciwwireless
Quantitative Biology Bootcamp/Lab I
2 September 2025
30,000 ft Overview
Introductions
Rajiv
Mike
Fred
Lance
Sneha
Sadhana
Design by Rebekka Paisner
James Taylor (1979-2020)
What? Short Overview
Quantitative and computational methods are increasingly essential to all sub-disciplines of modern biological research. The goal of this intensive week-long “boot camp” is to empower students with the fundamental skills to apply these methods, as well as connect them to resources for further developing their knowledge and abilities.
The class starts at 9 am with formal instruction ending at 5 pm daily. The course demonstrates the importance of version control, documentation, testing, and other methods for enhancing reproducibility, reliability, and useability of software. This is achieved through live coding sessions and use of active learning exercises, where for the majority of the class, students perform data analysis to address biological questions and reinforce core bioinformatic concepts.
Why? Modern biology is data intensive
Large scale data acquisition has become easy,
e.g. high-throughput sequencing and imaging
Experiments are increasingly complex
Making sense of results often requires mining and making connections across multiple databases
Nearly all high-profile research involves some
quantitative methods
The methods section of a paper should provide sufficient detail to reproduce an experiment.
The methods section of a paper should provide sufficient detail to reproduce an experiment.
For computational research, you can go a step further: provide the raw data and the code.
The methods section of a paper should provide sufficient detail to reproduce an experiment.
For computational research, you can go a step further: provide the raw data and the code.
How has this worked in practice?
Spectrum of Reproducibility
Our Goals
Become comfortable using and writing software
to work with large-scale biological data.
Be able to reuse and reproduce analyses.
Understand the importance of tools and
practices like version control and apply them.
Get some initial exposure to key data analysis
problems and be prepared to approach a wide variety
of data analysis problems throughout the coming year.
Learning Objectives
Three Parts to Our Training Strategy
bedtools.readthedocs.io // bioconductor.org/packages/DESeq2 // pubmed.gov/22068540 // learner.org/series/engineering-towers-elementary-school-educator-curriculum/group-presentation
Bootcamp
Core Labs
Project Work
Quantitative Biology Bootcamp
Tuesday
Python Basics using Notebooks
Wednesday
Python FileIO + dicts, transitioning to Unix + Scripts
Thursday
git and practice
with Mini-Project #1 and #2
Friday
R for data analysis, plotting, and Bioconductor
Quantitative Biology Core Labs
Computational Algorithms
Genomic Workflows
Statistical Analyses
Quantitative Biology Project Work
Independent 🐣
Develop your own project e.g. reproduce a figure, compare two methods
Feedback 🏋️♀️
Open science on GitHub, Instructors and TAs,
Peer Review
Groups 👨👩👧👦
Self-assemble
into teams of 2
Deliverables ✅
Proposal,
Check-in #1 + #2,
Final Presentation
Example Projects from Quantitative Biology 2024
For Those with Prior Experience
Prior Experience of CMDB 2025 Cohort (n=24)
Bootcamp Logistics
Four-Day Agenda
Tue
Wed
Thu
Fri
Python: data types, control structures, etc.
Python: file i/o, dictionaries; Unix, Python scripts
Review; Git; Mini-project #1 and #2
R: tabular data analysis, plotting, Bioconductor
Daily Agenda
Attendance
Students should not participate in any other meetings, courses, or lab work throughout the week.
Please be on time for course activities, and budget extra time in anticipation of technical delays.
Please let us know about any emergencies, family responsibilities, illness, etc. that may prevent attendance, and we will work to accommodate reasonable requests.
Do not come to class if you are feeling sick. There will be no penalty for such absences, and we will work with you to make arrangements for catch-up work if you are too sick to participate.
For Biologists with No Python/Unix Experience
Guidelines and Expectations
Technology
Computational Tools
Terminal
VS Code
RStudio
Communication Tools
Slack
Documentation and help
Ready Your Laptops
Log into GitHub
Password and Two-factor auth
Check into #quantbio_2025
React “green sticky” and reply to thread
Start
Tools
Terminal, RStudio, VS Code
WiFi: carnegie / ciwwireless