JABBA vs Jabba: when is software not really software?

It was only a matter of time I guess. Today I was alerted to a new publication by Simon Cockell (@sjcockell), it's a book chapter titled:

From the abstract:

Recently, a new hybrid error correcting method has been proposed, where the second generation data is first assembled into a de Bruijn graph, on which the long reads are then aligned. In this context we present Jabba, a hybrid method to correct long third generation reads by mapping them on a corrected de Bruijn graph that was constructed from second generation data

Now as far as I can tell, this Jabba is not an acronym, so we safely avoid the issue of presenting a JABBA award for Jabba. However, one might argue that naming any bioinformatics software 'Jabba' is going to present some problems because this is what happens when you search Google for 'Jabba bioinformatics'.

There is a bigger issue with this paper that I'd like to address though. It is extremely disappointing to read a software bioinformatics paper in the year 2015 and not find any explicit link to the software. The publication includes a link to http://www.ibcn.intec.ugent.be, but only as part of the author details. This web page is for the Internet Based Communication Networks and Services research group at the University of Gent. The page contains no mention of Jabba, nor does their 'Facilities and Tools' page, nor does searching their site for Jabba.

Initially I wondered if this is paper is more about the algorithm behind Jabba (equations are provided) and not about an actual software implementation. However, the paper includes results from their Jabba tool in comparison to another piece of software (LoRDEC) and includes details of CPU time and memory requirements. This suggests that the Jabba software exists somewhere.

To me this is an example of 'closed science' and represents a failure of whoever reviewed this article. I will email the authors to find out if the software exists anywhere…it's a crazy idea but maybe they might be interested if people could, you know, use their software.

Update 2015-11-20: I heard back from the authors…the Jabba software is on GitHub.

ACGT is now AFCW (Approved for Free Cultural Works): thoughts on switching to a CC-BY license

This website, as well as my personal website and Rescued by Code, licenses material under a Creative Commons license. Specifically, I've been using the Attribution Non-Commerical license, popularly known as CC BY-NC. My joint venture with Abby Yu, The Take-Home Message web comic, has been even more restrictive and has been licensing content under the Attribution Non-Commercial Share-Alike license (CC BY-NC-SA).

These choice of licenses is something that's been on my mind for a while. I've known that I'm not being as open as I could be and maybe this has stemmed from an unwarranted (not to mention unlikely) fear that someone would take all my blog posts and somehow seek to profit from them.

Today I saw a tweet by Rogier Kievit (@rogierK) that has helped me change my mind:

I found the third link — something that is now over a decade old — particularly persuasive and accordingly I have switched all of my website licenses to CC-BY. Apparently this means that all of my writings now fall into the category of Free Cultural Works. I am grateful to Abby Yu to agreeing to this change for The Take-Home Message.

This change also means that someone can now use my blog posts to write the definitive book on JABBA-awards…just as long as they give me appropriate attribution.

101 questions with a bioinformatician #36: Alicia Oshlack

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.

Alicia Oshlack is the Head of Bioinformatics at the Murdoch Childrens Research Institute (they don't like apostrophes) in Melbourne, Australia. Her research focuses on four main project areas: methods for analysing RNA-seq data, epigenomics, clinical genomics data analysis, and cancer genomics.

Before moving into the field of genomics, Alicia had a background in astronomy and her Ph.D. work concerned the structure of radio quasars. Not many bioinformaticians can claim to have published papers on the topic of estimating the mass of black holes!

You can find out more about Alicia by reading her Wikipedia page or by following her on twitter (@AliciaOshlack). I also encourage you to check out her must read article for fellow computational biologists: A 10-step guide to party conversation for bioinformaticians. And now, on to the 101 questions...



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

I love the pace at which things are changing in the field. There is always something new to work on and there are so many ways to contribute something useful to the research community. I also really love the balance between collaborative analysis on really interesting biological problems and doing careful methods development.



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

I get frustrated that I need to spend so much of my time convincing people that bioinformatics is a real scientific research discipline where we have deep scientific training and use our brains to solve scientific problems. Hopefully I will have convinced everyone in Australia soon.



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?

I did my PhD in astrophysics and I often wonder if I would have been better off doing a more relevant subject but I really appreciate the skills I learnt doing that. Within this I probably would tell myself to put a bit more focus on programming and do statistics instead of applied mathematics.



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

I think limma is amazing. Have you seen the users guide? I think it's 145 pages long and although it was originally developed for microarray analysis more than 12 years ago it has adapted to the sequencing revolution and is used more than ever now. I believe it is the most widely used bioconductor analysis package ever.



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?

I think S = G/C because I'm always a little bit biased.