Data science and bioinformatics tutorials
Tag: glm
It has been well over a year since my last entry, I have been rather quiet because someone has been rather loud 👶 Just last week I found some time to rewrite a draft on gradient descent from about two years ago, so here we are - back in business! Gradient descent is a fundamental … Continue reading Gradient descent in R
Statistical models generally assume that All observations are independent from each other The distribution of the residuals follows $latex \mathcal{N}(0, \sigma^2)&s=1$, irrespective of the values taken by the dependent variable y When any of the two is not observed, more sophisticated modelling approaches are necessary. Let's consider two hypothetical problems that violate the two respective assumptions, … Continue reading Linear mixed-effect models in R
This time I elaborate on a much more specific subject that will mostly concern biologists and geneticists. I will try my best to outline the approach as to ensure non-experts will still have a basic understanding. This tutorial illustrates the power of genome-wide association (GWA) studies by mapping the genetic determinants of cholesterol levels using … Continue reading Genome-wide association studies in R
poissonisfish 