Warning: Please be aware that these videos are a snapshot, and as such may use an outdated version of the tutorial and/or Galaxy. Below the video you will find links to the tutorials as they appeared at the time of recording.
Regression in Machine Learning
Below are video tutorials for this GTN material, created for various (past) events.
Video (February 2021)
The talk includes a lecture followed by a hands-on session to apply multiple regression algorithms on the DNA-methylation dataset to predict biological age. In this tutorial, we will build a regression model for chronological age prediction, based on DNA methylation. This is based on the work of Jana Naue et al. 2017, in which biomarkers are examined to predict the chronological age of humans by analyzing the DNA methylation patterns. Different machine learning algorithms are used in this study to make an age prediction. It has been recognized that within each individual, the level of DNA methylation changes with age. This knowledge is used to select useful biomarkers from DNA methylation datasets. The CpG sites with the highest correlation to age are selected as the biomarkers (and therefore features for building a regression model). In this tutorial, specific biomarkers are analyzed by machine learning algorithms to create an age prediction model. Multiple visualisations are also used to analyse the predictions made by simple and complex regressors and hyperparameters of one of the regressors also optimised.