Bioinformatics

Understanding how kallisto works

In 2016,  Bray et al. introduced a new k-mer based method to estimate isoform abundance from RNA-Seq data.  Their method, called kallisto, provided a significant improvement in speed and memory usage compared to the previously used methods while yielding similar accuracy.  In fact, kallisto is able to quantify expression in a matter of minutes instead of hours.  Since it is so light and convenient, kallisto is now often used to quantify expression in the form of TPM.   But how does [...]

By | 2018-04-08T15:01:03+00:00 March 28, 2018|Categories: Bioinformatics, Data Analysis|1 Comment

Think like a computer

Let's say all your results for a given project are stored in Excel files named exp1.xlsx, exp2_20170708.xlsx, exp_prolif_072017.xlsx... Inside file exp1.xlsx, you have this : This might be a user-friendly result file but it is not "computer-friendly" file. Let's suppose that you (or your boss) decide that you now need a database instead of the twenty-six different Excel files you have been using to store results. If all your files are similar to exp1.xlsx, you will have to put a [...]

By | 2018-02-08T13:32:14+00:00 February 8, 2018|Categories: Bioinformatics, Biology|1 Comment

A multiprocessing example and more

Recently, I had to search a given chemical structure into a list of structures. Using the python chemoinformatics packages pybel and rdkit, I was easily able to do so but the operation took a little too much time for my linking. Wondering how I could search faster, I immediately thought about Jean-Philippe's previous blog post titled Put Those CPUs to Good Use. I've decided to follow his instructions and give it a try. Goal Look for a molecule (a given [...]

By | 2017-12-11T12:55:55+00:00 December 11, 2017|Categories: Bioinformatics, Computer science, Performance|0 Comments

Let Your Data Flow: Streams and Reactive Programming

What's all this about ? ReactiveX is a combination of the best ideas from the Observer pattern, the Iterator pattern, and functional programming. Using Rx, you can easily: - Create event or data emitting streams from sources such as a file or a web service - Compose and transform streams with query-like operators - Subscribe to any observable stream and "react" to its emissions to perform side effects Reactive programming has been gaining traction these past few years. Maybe you've [...]

By | 2017-05-03T09:19:14+00:00 May 2, 2017|Categories: Bioinformatics, Computer science, Data Analysis|Tags: , |2 Comments

SNP Filtering with pyGeno

Looking over the contents of our growing blog (good job guys !), it occured to me that we had not yet posted an article pertaining to the fantastic (and homegrown !) bioinformatics resource that is pyGeno. It turns out I need to use pyGeno to generate data and it's also my turn to write a blog post, how convenient ! I'll focus the article on writing a SNP filter, which can be a bit surprising the first time you try [...]

By | 2017-04-29T17:57:51+00:00 December 9, 2016|Categories: Bioinformatics, Python|Tags: , |0 Comments