New Lab Member Reading (Onboarding) - CoBrALab/documentation GitHub Wiki

Computers

Software Carpentry Lessons covers the shell, R, python and git.

Additional resources from SciNet's Virtual Summer Training Program: (free for SciNet/Niagara users, usually runs from June-August - would highly recommend signing up for any courses that interest you!)

Intro to supercomputing (+ Niagara)
Advanced intro to the Linux command-line interface (NOTE: this video assumes some knowledge about the basic commands for working with files and folders; please refer to the Software Carpentry lesson on the Unix Shell for a comprehensive beginner-oriented tutorial)

The SciNet YouTube Channel has videos for the other courses of the Virtual Summer Training Program as well, most of which build on knowledge from the two above.

A text-based mystery to learn bash Command line mystery

The Pirates Guide to YaRrr

Intro to data preprocessing in Python; log in to CIC computer and navigate to the following directory: /data/chamal/projects/nadia/intro_data_preprocessing_python

Preparing/processing raw T1w scans for brain structural analyses: Where to start

A common starting point for new T1w MRI projects is comparing cortical macrostructural measures (cortical thickness, surface area, etc.) between individuals or groups. If you have a raw dataset that you're not sure what to do with, below are links to our documentation for the typical workflow steps for transforming it into a useful format and obtaining the basic processed outputs we use for statistical analyses. QC = quality control

Manual motion QC of raw T1w volumes
Image preprocessing using minc-bpipe-library (outputs include things like brain masks and bias field-corrected brain volumes, which can improve the performance of any subsequent processing/analysis pipelines, like CIVET and MAGeT)
Image processing for cortical surface extraction and analysis: running and QCing outputs of the CIVET pipeline

Most structural MRI tools used in the lab require that your images be in MINC format. See here for how to convert different file types to .mnc.