Introduction to Biological Data Analysis
Instructors: Christopher Hemme, PhD, University of Rhode Island and Jillian Wise, PhD, Salve Regina University
Location: URI
Session 1: June 23-25 (Avedisian 205)
Session 2: July 14-16 ( Avedisian 205)
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) | Experimental Design and Power Analysis for Determining Sample Size for Biomedical Experiments (Lecture and Hands-On) | Single Cell Identification (Hands-On) |
| 10:00 AM-11:00 AM | Using the Unix Command Line and Interactive Tools (Jupyter Notebooks and RStudio) on High-Performance Computing Clusters (Hands-On) | Methods for Exploratory Analysis of Biomedical Data (Lecture and Hands-On) | Exploratory Analysis of Single Cell Data (Hands-On) |
| 11:00 AM-12:00 PM | R Programming I – Basic Data Structures and Functions (Hands-On) | Statistical Methods for Analysis of Biomedical Data (ANOVA, t-Test, linear regression, logistic regression) (Lecture/Hands-On) | Artificial Intelligence in Biomedical Data Analysis (Optional, if time allows) |
| 12:00 - 1:00 PM | Break | Break | WDT Survey and Certificate Distribution |
| 1:00 PM-2:00 PM | R Programming II – Tidy Data and Tidyverse (Hands On) | Introduction to Bioinformatics and Single Cell Omics (Lecture) | |
| 2:00 PM-3:00 PM | R Programming III – Data Visualization (Hands On) | Processing of Single Cell Data (Hands-On) | |
| 3:00 PM-4:00 PM | Basic Statistical Concepts for Biomedical Research | Processing of Single Cell Data Cont. (Hands-On) |