Trying to locate the source of duplicated software names

Thanks to Andrew Su (@andrewsu) and Mick Watson (@BioMickWatson) for alerting me to the following:

The former paper is from 2009, the latter paper is from 2015. Neither paper has anything to do with this 2010 paper which introduced something called the Genome Positioning System (GPS). Most importantly, none of these papers have anything at all to do with GPS (as most people understand the term).

If I run a Google search for GPS Bioinformatics the top hit that I see is for the MSc course in Bioinformatics as part of Brandeis University's Graduate Professional Studies program.

The usual disclaimer applies:

  1. Check existing literature before you name your software (at the very least run a Google search).
  2. Double check the name by adding the word 'bioinformatics' or 'genomics' to the search terms.
  3. Avoid names which wholly or partially contain words or terms that have nothing to do with your software.

Freely & Unrepentantly Confessing to Heresy →

There is a new post by Keith Robison in which he comments on my Excel/Bioinformatics post from August 28th:

Keith Bradnam reported a huge influx of traffic for a recent post -- not surprising, since he labeled it NSFW (Not Safe For WorK)… Bradnam was, of course, kidding. His short item showered derision on a recent Microsoft announcment about importing sequences into Excel.

The spike in traffic really has been insane. The post has become my most viewed post of anything I have ever written on this blog (by quite a margin). Clearly I have tapped into some anti-Microsoft (or just anti-Excel?) sentiment.

Keith Robison then takes on the 'case for the defense' and makes some fair points about Excel:

But to dismiss Excel as unworthy of any use in bioinformatics is to miss the fact that buried under the residue of years of creeping featurism is a tool useful in specific contexts and with some key advantages. The first advantage is that it is ubiquitous…

He then goes on to include some legitimate examples of how you might want to use Excel in order to work with sequence data.

I will conclude by saying that I bear no ill feelings towards Excel users, even those using it for bioinformatics! I have also used Excel in the past for trying to analyze some bioinformatics data. This was using Excel 2004 for Mac which suffered from a 32,000 row limit which made it unsuitable for incorporating some datasets. It was this limitation that was partly the impetus for me to start learning how to do some things in R.

Fundamentally, I feel that Excel is not a great tool for bioinformatics because: it is not open, it is not obviously workable as part of any standard bioinformatics pipeline, and it is not available on Linux (where a lot of bioinformatics happens). But, as always, you should use the tools that help you get the job done.

Why I still think people should be jumping on the ORCID bandwagon

Adapted from photo by flickr user nanoprobe67

Adapted from photo by flickr user nanoprobe67

So I wrote this tweet…

Which triggered a lot of twitter discussion.

Which led to this blog post by Mick Watson.

Which led to more discussion on twitter.

Which led to this blog post by Brian Kelly.

Which leads us to this blog post…

Much of what I was going to say has already been said by others (I especially encourage readers to jump straight to Brian Kelly's blog post), but I wanted to add a few comments…

This is bad

A tremendous, mind-boggling, and frustrating number of hours are lost every year by people performing mindless, thankless, and painful academic administration tasks. A lot of of this work is stuff that happens 'behind the scenes', but which is essential for science to happen. Processes such as grant renewals often have to pull together all of the papers generated over the preceding grant period, and connect those papers to the researchers who were on the previous grant (and who may be named on the renewal grant). For a large research center with 100s of PIs this can involve a lot of work (tracking 100s of publications), and ultimately can end up relying on a lot of emails being sent to individual PIs. The problems get worse in those situations where people's names have changed and/or have submitted papers using slightly different formats to their names.

All of this pain is because we don't have unique identifiers for academic researchers that are consistently used across all parts of the academic system.

In taxonomics we are blessed with the widespread adoption of NCBI's taxonomy IDs. This means that I could write a publication in which I choose to describe Mick Watson as belonging to species NCBI TaxID 9606 and others would be able to work with that data. Indeed, I can go UniProt and browse species 85621 and know that this will be the same ID as used at NCBI (and many other places).

Species names can, and do, sometimes change (remember Fugu rubripes?) and biological research would be in a mess if we didn't have standardized identifiers for species. The same should be true for academics. No-one should have to waste time checking whether this 2015 paper by 'M Watson' is the same author as in this 2015 paper by 'M Watson' (this type of problem is greatly compounded for certain names).

This would be nice

I envisage a future where any publication that I contribute to is connected to my ORCID ID (strictly just 'ORCID'). Furthermore, any grant that I am named on should use the same ORCID. But why stop there? Why not connect all of my scientific endeavors? GitHub accounts could be connected to ORCID to tag all of my scientific coding with the same ID. Publish research slides on Figshare or Slideshare? Why not use ORCID? Even blog posts like this one could potentially be connected to the wider universe of ORCID-tagged material.

This is why I originally tweeted my excitement about the adoption of ORCID by arXiv. I want to see ORCID everywhere. Once ORCID gains critical mass by being adopted by enough 'key' services, then the ORCID bandwagon can really start to accelerate.

How I see ORCID being used

Echoing the views of Brian Kelly (and others), I just see ORCID primarily as a service to generate the unique ID and then act as a central authentication server for any other service that may wish to also use ORCID. In many ways, ORCID then acts like twitter, Google, and Facebook in letting you have a single sign-on system across multiple sites. Except ORCID is open and will not be mining your data to sell you stuff.

I have no interest in maintaining an ORCID page of publications. I want others to use the ORCID API to build clever tools that will leverage all of the rich information that could come about when you connect people to all of the scientific output that they have helped create. If Mick Watson ever decides to start being known as Sir Michael of Grimsby, and if he switches from using GitHub to BitBucket, this should not be a barrier from someone using the ORCID API to write a tool that generates a list of 'All of Mick's Public Code'.

ORCID may not succeed, but the promise of what it could deliver is so important that we should all give it the benefit of the doubt and try to make it work. If you have problems with ORCID, let them know. Most importantly, if you don't yet have one you should register for your ORCID identifier now! It is an open platform, run by a non-profit organization (these are good things). It takes just 30 seconds, and apart from those 30 seconds you have nothing to lose.

Twenty years of bacterial genome sequences

Take-Home Message comic #5 celebrates an amazing milestone. During my PhD, I kept a little list pinned to the filing cabinet next to my desk, a list which contained details of every sequenced genome. This was something that was much easier when the number of published genomes was still in the single digits!

This is my favorite Take-Home Message comic to date. I feel that we are slowly settling in on a style that works well for this medium, and Abby's drawings just seem to get better and better.