Bioinformatics

Good resources to learn R

Since it's the summer vacations, why not take some time to learn R. There are numerous free resources online to dive into this powerful language. For whomever wants to learn it, the challenge more related to finding the time rather than finding resources. Videos Coursera is an inevitable for online learning. There are a few good video courses offered for R beginners that are more or less oriented toward genomics : https://www.coursera.org/learn/r-programming https://www.coursera.org/learn/exploratory-data-analysis https://www.coursera.org/learn/bioconductor (Bioconductor is a life science packages [...]

By | 2016-11-08T09:30:04+00:00 July 11, 2016|Categories: Bioinformatics, R|0 Comments

SciPy and Logistic Regressions

Given a set of data points, we often want to see if there exists a satisfying relationship between them. Linear regressions can easily be visualized with Seaborn, a Python library that is meant for exploration and visualization rather than statistical analysis. As for logistic regressions, SciPy is a good tool when one does not have his or her own analysis script. Let's look at the optimize package                        from scipy.optimize import [...]

By | 2016-11-08T09:30:04+00:00 June 9, 2016|Categories: Bioinformatics, Data Analysis, Data Visualization, Python|0 Comments

The language(s) of bioinformatics

The most recurrent question I get regarding bioinformatics is unfortunately the one that leads to the least productive discussions I've participated in: Which programming language should I use for bioinformatics? Don't get me wrong, in a pub, over a beer, this can lead to some lively entertainment among the nerd intelligentsia... but rarely does it lead to enlightenment that persists in the morning! Here, I'd like to share the current answer I have honed over the past years. It is based [...]

By | 2016-11-08T09:30:05+00:00 April 18, 2016|Categories: Bioinformatics|0 Comments

Parallelize your Python !

This article will teach you what are multithreads, multicores, and in what circumstances each can be used. Your nerd friend keeps telling you about his professional deformation all the time? Wanting to parallelize and optimize his time? Do you wish to understand it as well and save time by parallelizing your programs in Python? Then this article is what you need! You will be able to gain big amounts of time, thanks to a small dose of parallelism [...]

By | 2016-11-08T09:30:06+00:00 March 29, 2016|Categories: Bioinformatics, Performance, Python|Tags: , , |0 Comments

Factorial and Log Factorial

Factorial: When you need to calculate n!, you have several solutions.  The "rush" solution: using a loop or a recursive function:  def factorial_for(n): r = 1 for i in range(2, n + 1): r *= i return(r) def factorial_rec(n): if n > 1: return(n * factorial_rec(n - 1)) else: return(1) Here, the multiplication of the numbers sequentially will create a huge number very quickly. This is good, but computers are faster when 2 small numbers (120x30240) are involved in a multiplication versus the [...]

By | 2016-11-08T09:30:06+00:00 February 22, 2016|Categories: Bioinformatics, Data Analysis, Performance, Python|0 Comments