In need of some bogus bioinformatics acronyms? Try these on for size…

Three new JABBA awards for you to enjoy (not that anyone should be enjoying these crimes against acronyms). Hold on to your hats, because this might get ugly.

 

1: From the journal Scientific Reports

The paper helpfully points out that the name of this tool is pronounced 'Cadbury'. I'm not sure if they are saying this to invite a trademark complaint but generally I feel that it is never a good sign when someone has to tell you how to pronounce something. The acronym CADBURE is derived as follows:

Comparing Alignment results of user Data Based on the relative reliability of Uniquely aligned REads

On the plus side, CADBURE mostly uses the initial letters of words. On the negative side, only six out of the fifteen words contribute to the acronym and this is why it earns a JABBA award.

 

2: From the journal BMC Bioinformatics

SPINGO is generated as follows:

Species-level IdentificatioN of metaGenOmic amplicons

So only two words contribute the initial letters, 'identification' donates its second N (but not its first), and 'amplicons' gives us nothing at all. Very JABBA-award worthy.

 

3: From the journal Bioinformatics (h/t to James Wasmuth)

It is very common for people to wait until the end of the Introduction before they reveal how the acronym/initialism in question came to be, but in this paper they don't waste any time at all…it's right there in the title.

It is the mark of a tenuously derived acronym when the initial letter of a word isn't used, but the same letter from a different position in the same word is used, e.g. the second 'R' of 'regression'.

While the code for HEALER is available online, none of the five C++ files contain the word HEALER in their name or anywhere in their code. Nor is there any form of README or accompanying documentation. This is all that you see…

Congratulations to our three worthy JABBA award winners!

101 questions with a bioinformatician #35: Aaron Darling

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.

Aaron Darling is an Associate Professor at the ithree institute — where capital letters are in short supply? — which is part of UTS (University of Technology Sydney). His research focuses on developing computational and molecular techniques to characterize the hidden world of microbes. He helped develop the Mauve multiple genome alignment tool and continues to work on this and other software tools. Aaron also has a long-standing interest in poop:

Of course this interest is all part of an ongoing research project, one that is seeking to understand the development of the infant gut microbiome.

You can find out more about Aaron by visiting his lab's website, or by following him on twitter (@koadman). And now, on to the 101 questions...



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

The growing interplay between informatics, molecular biology, and experimental design is very exciting. In the past 10 years many problems that could only have been solved through decades of experimental work have been transformed from experimental problems to data analysis problems. I think this trend will only accelerate as our technology to interface digital computational systems with biological systems continues to improve. And data analysis feeds back to inspire new experimental designs in a feedback loop that's getting ever-shorter. As an informatician I find it especially fun to discover new ways of designing the lab work that solves long-standing data analysis problems.



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

Data wrangling and data mangling. This is almost certainly cliche by now but inconsistently implemented file formats are the bane of bioinformatics. This was apparent to me within weeks of starting in the field, as my first assigned task was to write a sequence file format parsing library for the E. coli genome project team. I often wonder why I didn't run as fast as I could in the opposite direction.



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

Early on I benefited from a nugget of wisdom in Dan Gusfield's sequence analysis book which emphasized the importance of solving biological data analysis problems that are core to the biology, not the technology platform used to measure the biology. For example the general sequence alignment problem vs. short read alignment. Those are the contributions that are going to matter over the long term. I wish I had also appreciated early on that the elegance and simplicity of the solution, and especially the code implementing it, matters just as much.



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

Probably BEAST, because I learned so much about phylogenetic models, MCMC, and software design from using it and coding up modules for it.



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

H, because as a teenager I always wanted to be a G but in reality was everything but.

We have not yet reached peak CEGMA

I was alerted to some disturbing news this weekend: CEGMA won't die!

CEGMA is a tool that I helped develop back in 2005. The first formal publication that describes CEGMA came out in 2007, and since then it has seen year-on-year growth in the number of citations to this paper.

I keep on thinking that this trend must end soon, and I was therefore hopeful that 2014 might have been the year of peak CEGMA. There were three reasons why I thought this might happen:

  1. CEGMA is no longer being developed or supported
  2. I have used the PubMed page for the CEGMA paper to advocate that people should no longer use this tool
  3. CEGMA is heavily reliant on an — increasingly out-of-date — database of orthologs that was published in 2003

However, despite my best wishes, Google Scholar has revealed to me that 2015 has now seen more citations to the CEGMA paper than in any previous year:

CEGMA citation details from Google Scholar

I'm hopeful that the development of the BUSCO software by Felipe Simão et al. will mean that 2015 will definitely be the year of peak CEGMA!

The next BioNano Genomics Webinar is about improving genome assemblies with gEVAL

The next BioNano Genomics webinar will be October 27th, 2015 at 8:00 am (PST). The title of the webinar is:

gEVAL- A Genome Evaluation Browser for Improving Genome Assemblies

The gEVAL browser is managed by the Genome Reference Informatics Team (GRIT) at the Wellcome Trust Sanger Institute. William Chow, the lead developer of gEVAL will be leading the webinar.

You can register for the event here.

 

Financial disclaimer: I do not own shares in any biotechnology company.