Skip to content
@DS3-2025

DS3 2025

README.md

Course Materials for Data Science for Developing Scholars in Down Syndrome Research (DS3) 2025

Main course website: https://includeds3.org/

The Data Science for Developing Scholars in Down Syndrome Research (DS3) course is a training program working to increase data sciences expertise across the INCLUDE Project and the Down syndrome research community.

Getting started with R and RStudio

Slides
GitHub repository: installing_updating_R-RStudio

Alternatives to running locally:
Posit Cloud
Cavatica
Apply for INCLUDE Cloud Credits

Introduction to the Tidyverse

Slides
GitHub repository: Rproject_template
GitHub repository: tidy_data_exercise

Morning sessions: Short Read Sequencing Workshop

Website: https://biodatasci.colorado.edu/shortread/
GitHub: Dowell-Lab/srworkshop

Afternoon sessions

Github (this site): DS3-2025

Day 1: The Human Trisome Project

Instructor: Matthew Galbraith
An overview of the Human Trisome Project and the journey from data to discovery.
Slides

Day 2: Omics and Data Science Concepts

Instructor: Matthew Galbraith
An introduction to important concepts in omics and best practices in data science.
Slides

Day 3: Reproducible data analysis using R and RStudio

Instructor: Matthew Galbraith
A guide to conducting reproducible data analysis in R using RStudio and tidy principles.
Slides
GitHub repository: Rproject_template

Day 4: Data Cleaning and Exploratory Data Analysis

Instructor: Matthew Galbraith
Exercises in data cleaning/wrangling in R using tidyverse principles and tools.
GitHub repository: intro_exploratory_data_analysis
GitHub repository: tidy_data_exercise

Day 5: Intro to Linear Regression and Hypothesis Testing in R

Instructor: Matthew Galbraith
An introduction to statistical modeling and testing in R
Slides
GitHub repository: linear_regression_exercise
GitHub repository: HTP_linear_regression_example

Day 6: Advanced Data Visualization and Analysis in R

Instructor: Matthew Galbraith
Examples and discussion of effective data visualization using ggplot in R.
Slides
GitHub repository: HTP_linear_regression_example
GitHub repository: HTP_DESeq2_analysis
GitHub repository: HTP_single_cell_dataviz_mass_cytometry

Day 7: Advanced Data Visualization and Analysis in R

Instructor: Jim Costello
Applications of simple machine learning methods to predict outcomes leveraging HTP datasets.

GitHub repository: Visualize_Cluster_HTP

Day 8: Supervised Machine Learning with HTP examples

Instructor: Jim Costello
Applications of simple machine learning methods to predict outcomes leveraging HTP datasets.

GitHub repository: PredictiveModels

Day 9: Analysis of INCLUDE data with R using Cavatica

Instructor: Matthew Galbraith and Velsera
Slides
A guide to locating data in the INCLUDE Data Hub and transfering to the Cavatica platform for analysis.
Apply for INCLUDE Cloud Credits
GitHub repository: HTP_linear_regression_Cavatica

Popular repositories Loading

  1. .github .github Public

    Public organization profile readme

    1

  2. installing_updating_R-RStudio installing_updating_R-RStudio Public

  3. Rproject_template Rproject_template Public

    R

  4. tidy_data_exercise tidy_data_exercise Public

    R

  5. Visualize_Cluster_HTP Visualize_Cluster_HTP Public

    Applications of simple machine learning methods to predict outcomes leveraging HTP datasets.

    HTML

  6. PredictiveModels PredictiveModels Public

    Applications of simple machine learning methods to predict outcomes leveraging HTP datasets.

    HTML

Repositories

Showing 10 of 13 repositories
View all repositories

People

This organization has no public members. You must be a member to see who’s a part of this organization.

Top languages

Loading…

Most used topics

Loading…