How to make your genomics website more suitable for an English-speaking audience

Today I visited the website of the Beijing Institute of Genomics (BIG) for the first time. BIG is not to be confused with BGI (which was formerly known as the Beijing Genomics Institute). If you look at just about any web page on this site other than the home page (which contains an unusual visual element), you'll see the following image:

My sharp, British-born, eyes quickly recognized this as the UK's Houses of Parliament in London (well technically it's the Palace of Westminster). See this image for a comparison. I then noticed that this image doesn't feature on the Chinese language version of the website (which has a completely different design).

I can only assume that some web designer thought that an image like this would be fitting because it is the English-language version of the website, and that they therefore chose an image of something (incorrectly) deemed to be English. At this point, I feel obliged to share the following video which offers a definitive explanation as to the differences between England, Great Britain, and the United Kingdom:

Reflections on my '101 questions with a bioinformatician' series

This is in lieu of a regular '101 questions with a bioinformatician' post which has been delayed (hopefully by only a day). This series of interviews has now been running for over 2 months and — judging by my web stats — it seems to be popular. In fact, these posts now account for the majority of traffic to this site.

Thanks to everyone who has contributed so far, and for everyone who has been reading these interviews. It's been fun doing this and I've enjoyed seeing the variety of answers that people have provided.

I should confess that I'm solely responsible for adding hyperlinks to the answers that people provide, and in addition to adding links for obvious items like pieces of bioinformatics software, I sometimes like to have a bit of fun with what I choose to link to. E.g. see the links I added to question 101 in my interview with Holly Bik.

To finish off, here are some relevant numbers about this series:

  • 10 — number of interviews posted
  • 2 — number of interviews finished and (almost) ready to be posted
  • 6 — number of people who have agreed to be interviewed but haven't yet sent me their answers (cough, cough).
  • 81 — my current list of 'potential interviewees'

The last point means that hopefully I can keep this series going for a while longer. I guess that I now have to aim for an interviewee #101, (which would be the 102nd interview…obviously).

Still collecting results for my survey about gender bias in bioinformatics

A quick post just to say that although I published some preliminary results from my survey about gender bias in bioinformatics, I left the survey live so that others could still add their responses. So far, I've had 28 more responses on top of the original 370. 

I also tweaked the survey form to allow ex-bioinformaticians to respond (and I asked whether they left bioinformatics as a career because of gender bias). If you haven't done so, please complete the form (embedded below) or available here. I'll try to update the main results on Figshare in a few weeks. Hopefully, with some more results it will be possible to see if there are other notable patterns in the results.

101 questions with a bioinformatician #9: Tuuli Lappalainen

This post is part of a series that interviews some notable bioinformaticians to get their views on various aspects of bioinformatics research. Hopefully these answers will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.


Tuuli Lappalainen is a Group leader at the New York Genome Center, an institution that's so new, that their Illumina HiSeq X Ten is counted as one of their older sequencing machines. In addition to having possibly the coolest logo for a genomics/bioinformatics institute, they also have an impressive set of green credentials. And did I mention that it's in New York, New York? Start spreading the newwwss…

Sorry, I got distracted.

Tuuli is also an assistant professor at the Department of Systems Biology at Columbia University. Her work focuses on using high-throughput sequencing data to study functional genetic variation in human populations. Her website — paraphrasing Dobzhansky — puts it like this:

Nothing in the genome makes sense except in the light of the transcriptome

You can find out more about Tuuli by following her on twitter (@tuuliel) or by checking out her lab's website. Oh, and Tuuli is looking for a talented post-doc to join her lab (she didn't ask me to say that, it's all part of the service). And now, on to the 101 questions...

 

 

001. What's something that you enjoy about current bioinformatics research?

I have very little interest in methods for the sake of methods; for me it's all about understanding biology, and bioinformatics provides fantastic opportunities for that.

 

010. What's something that you *don't* enjoy about current  bioinformatics research?

The working environment that is local when data and analyses are increasingly global is driving me insane. I've done (and still do) a lot of consortium work, where all of us still end up copying large data files to our local servers, and having locally optimized pipelines and scripts that are impossible to transfer to colleagues. I know that many people are trying to solve the problem, and I hope we'll be able to make it happen soon. And then there are the complications of applying and getting access to various datasets. Privacy concerns are important, but does dbGap really need to be so difficult to use? Our open access data set from GEUVADIS (Genetic European Variation in Health and Disease) is a great exception to this.

 

011. If you could go back in time and visit yourself as an 18 year old, what single piece of advice would you give yourself to help your future bioinformatics career?

Learn more stats, math, proper programming. It's great to see how the younger generations have formal training in so many of the skills that I've had to just pick up the along the way — I'm a biologist by training and proud of it, but in the early 2000's computational biology was still very marginal. 

 

100. What's your all-time favorite piece of bioinformatics software, and why?

My two current favorites are pysam for handling BAM/SAM files — fast, great syntax, and much more versatile than alternatives — and Matrix eQTL for very fast eQTL analysis.

 

101. IUPAC describes a set of 18 single-character nucleotide codes that can represent a DNA base: which one best reflects your personality?

T for Tuuli!