Introduction to Biological Data Analysis
Instructor: Christopher Hemme, PhD, University of Rhode Island
Location: URI
Session 1: June 23-25 ( Location 205 Avedisian Hall)
Session 2: July 14-16 ( Location 205 Avedisian Hall)
Course Overview
This WDT Module aims to train students in basic methods of biological data science. It will cover concepts in using the Unix command line in a high-performance computing environment, introduction to the R programming language, design of biomedical experiments, and basic statistical analyses (e.g. t-test, ANOVA, regression). Finally, students will get a basic introduction to bioinformatics and omics methods. The module will be completed over 2.5 days and participants who complete the module will receive an RI-INBRE Certificate of completion.
Learning Outcomes
- Learn how to use the Unix command line on URI’s Unity High-Performance Computing Cluster
- Learn basic concepts in biomedical experimental design, such as selection of controls, determining proper sample sizes, and different experimental setups
- Process different types of biomedical data using common statistical concepts such as t-test, ANOVA, and linear regression
- Learn basic concepts in bioinformatics including omics data analysis
- Analyze bioinformatics data using established methods such as differential expression analysis
Lab Report
Students will be expected to maintain detailed laboratory notes to include:
- Data analysis protocols (e.g., workflows, software used, etc.)
- Quality control metrics for sequencing and data analysis
- Results of data analysis
Resources Used in this Module:
- Jupyter Notebooks for Hands-On Bioinformatics Data Analysis
- Slide Decks for Lectures
Proposed Timeline (subject to change)
| Day 1 | Day 2 | Day 3 | |
|---|---|---|---|
| 9:00 AM-10:00 AM | Introduction to Best Practices in Biomedical Data Science (Lecture) | Basic Statistical Concepts for Biomedical Research | Introduction to Bioinformatics and Omics |
| 10:00 AM-11:00 AM | Using the Unix Command Line on High-Performance Computing Clusters (Hands-On) | Introduction to Experimental Design | R Programming IV – BioConductor (Hands-On) |
| 11:00 AM-12:00 PM | Using Interactive Tools (Jupyter Notebooks and RStudio) and Data Science Modules on Unity (Hands-On) | Using Power Analysis for Determining Sample Size for Biomedical Experiments (Lecture and Hands-On) | Bioinformatics Data Analysis (Hands On) |
| 12:00 - 1:00 PM | Break | Break | WDT Survey and Certificate Distribution |
| 1:00 PM-2:00 PM | R Programming I – Basic Data Structures and Functions (Hands-On) | Methods for Exploratory Analysis of Biomedical Data (Lecture and Hands-On) | |
| 2:00 PM-3:00 PM | R Programming II – Tidy Data and Tidyverse (Hands On) | Statistical Methods for Analysis of Biomedical Data (ANOVA and t-Test) (Lecture/Hands-On) | |
| 3:00 PM-4:00 PM | R Programming III – Data Visualization (Hands On) | Statistical Methods for Analysis of Biomedical Data (Linear and Logistic Regression) (Lecture and Hands-On) |