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🦆🦆 Quality Control of NGS samples 🦆🦆

COVID-19 risk predictor developed for UAB hackathon

This project stores skeleton code, data, and instructions for labs written for the R component of the GRD 770 course taught in Fall 2019.

This project is dedicated to using various linear and nonlinear machine learning algorithms to create a model of cortical thickness as a function of various anatomic and retinotopic properties in early visual cortex.

This tutorial allows user to run parallelism using bash scripts and array jobs. Also it contains parallel scripts for matlab and R