Introduction to Linear Regression

A data scientist's first goal is to find underlying relations within the variables of a dataset. Several statistical and machine learning methods can be used to discover such relations. Once uncovered, this information can be applied to everyday problems. For example, in clinical medicine, a predictive model based on clinical data can help clinicians guide a patient's treatment by offering insights that might not have otherwise been taken into account. Simple linear regression One of the most basic methods available to [...]

A javascript implementation of the non-central version of Fisher’s exact test

In a previous post, I presented a case for choosing a non-central version of Fisher's exact test for most of bioinformatics' uses of this test. I will now present an implementation of this test in javascript that could easily be embedded in web interfaces. Although javascript is probably the least likely language to implement statistical methods, I hope this article will fill in as many details as possible to make it trivial to port it to other languages if the need arises. At [...]

By | 2017-04-29T17:47:57+00:00 January 13, 2017|Categories: Data Analysis|Tags: , , |0 Comments

Tweaking Fisher’s exact test for biology

Fisher's exact test is widely applied in bioinformatics (it is the core computation in gene-set or pathway enrichment analysis).  I won't introduce the test itself as others have done it several times (here), but will rather point to a disconnect between what it does and what is often needed. In Fisher's exact test, the null hypothesis is that there is no enrichment between the two variables studied.  When using this test with large numbers (such as the number of genes [...]

By | 2017-05-01T10:33:14+00:00 December 8, 2014|Categories: Bioinformatics, Biology, Statistics|Tags: |0 Comments