ITCR OPEN - Software Metrics Analyses Website

A summary of our findings from the 2024 State of the AnVIL user poll.

📚 An auto-generating library of Data Science Lab Github-based content

You will expand your current knowledge of Git and GitHub to help your research be more collaborative, reproducible, and transparent.

You will learn how to use Git, a version control system that is the primary means of doing reproducible and collaborative research. You will use Git from the command line to document the history of your code, create different versions of your code, and share your code with an audience via GitHub!

Fluency in programming and data science requires using computer software from the Command Line, a text-based way of controlling the computer. You will go on a guided under-the-hood tour behind the graphical interface we typically use: you will learn how to interact and manipulate files, folders, and software via the Command Line.

The course continues building programming fundamentals in R programming and data analysis. You will learn how to make use of complex data structures, use custom functions built by other R users, creating your own functions, and how to iterate repeated tasks that scales naturally.

The course covers fundamentals of R, a high-level programming language, and use it to wrangle data for analysis and visualization. The programming skills you will learn are transferable to learn more about R independently and other high-level languages such as Python.

Repo for Quarto based Open-source Tools for Training Resources (OTTR)

"Developing WDL Workflows" shows a bioinformatics workflow developer how to strategically develop and scale up a WDL workflow that is iterative, reproducible, and efficient in terms of time and resource used. This guide is flexible regardless of where the data is, what computing resources are being used, and what software is being used.