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Guillaume Filion
Randomness is an attitude
Randomness is an attitude

Guillaume Filion's posts

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Here is our latest work on Hi-C normalization

"We observed that current normalization methods are not robust to the presence of large-scale copy number variations, potentially obscuring biological differences and enhancing batch effects. To address this issue, we developed an alternative approach designed to take into account chromosomal abnormalities."

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In this article we discuss the most current challenges of data storage and organization. The literature is mostly concerned with defining standards, but little attention is paid to why people do not follow them.

Here, we follow the fate of a medium-size project and discuss the everyday issues of their members, and the solutions they can use in practice. The narrative is largely auto-biographic, but many researchers will recognize some of their own difficulties. Our hope is that this will help the community understand where the problems lie (lack of communications between experimenters and analysts, high turn over of laboratory members, lack of long-term planning for analysis and lack of awareness for standardization), and that it will help researchers implement solutions that work in their organization.


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Here is the third part of my tutorial on Burrows-Wheeler indexing methods. In this post I show a running C implementation of the algorithms, including compression. This also highlights the main ideas of the method and show why it is efficient.

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This is the second chapter of my tutorial on Burrows-Wheeler indexing methods. Here I show a commented implementation in C of the basic method. Very useful for beginners who want to understand how this all works in practice.


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New post on the Lab web site by +Heng-Chang CHEN . This gives some context of what we discovered about HIV, and how we found it.

"Whether the chromatin context influences HIV latency has been a long-standing question. Due to the lack of a proper technology, there was practically no progress since the question was raised. At the end of 2013, Guillaume and me came up with the idea to create a technology to answer this question."

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Our latest work has been published! In this article, we stumbled upon the role of genome architecture to optimize gene expression in Drosophila.

"The proper function of housekeeping genes relies not on contacts with long distance enhancers but on spatial clustering. Overall our results suggest that spatial proximity between genes increases their expression and that the linear architecture of the Drosophila genome contributes to this effect"


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My last blog post about scientific models and the difficult that humans sometimes have with them.

"I recently realized that I had no idea how Darwin stood against creationism and how he defended his view in regard of the doxa of his time. Digging into this topic turned out to be one the most important lessons I learned about the scientific method... and the lack of it."


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A blog post where I explain my opinion about panel interviews in the academia (backed up by some data).

"I was very surprised that the top candidates often proved less productive than those we had ranked mediocre. How was this possible at all? Panels are unbiased, they combine multiple expertises, they allow for critical discussion, so they should be able to pick the best candidates... right?"

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"We learned a great deal about how to organize such peer coaching sessions in the academia and how to make the best of them, but this is not what this post is about. Instead, I would like to share more important lessons I have learned about working together and using the group as support and source of motivation."


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How to choose if your statistical tests should have one or two tails? This blog post in dialogue form helps understand some of the caveats.

"Imagine that I want to prove that male crocodiles are bigger than females. I set up a one-tailed t test and it turns out that females are a whooping thirty percent bigger than males. What is my conclusion?
— I guess you conclude that females are actually bigger.
— Wrong. I conclude that females have exactly the same size as males.
— But you just told me that they are bigger!
— Yes, and I also told you that I am doing a one-tailed t test.
— That does not make any sense."

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