ORCID: binding the (academic) galaxy together

Adapted from picture by flickr user Jim & Rachel McArthur

I am a supporter of ORCID's goals to help establish unique identifiers for researchers. Such identifiers can then be used to help connect a researcher with all of their inputs and outputs that surround their career. Most fundamentally, these inputs and outputs are grants and papers, but there is the potential for ORCID identifiers to link a person to much more, e.g. the organisations that they work for, manuscript reviews, code repositories, published slides, even blog posts.

For ORCID to succeed it has to be global and connect all parts of the academic network, a network that spans national boundaries. On this point, I am very impressed by the effort that ORCID makes in ensuring that their excellent outreach materials are not only available in English. As shown below, ORCID's 'Distinguish yourself' flyer is available in 9 different languages. Other material is also available in Russian, Greek, Turkish, and Danish. If your desired language is not available, they welcome volunteers to help translate their message into more languages. Email community@orcid.org if you want to help.

Welcome to the JABBA menagerie: a collection of animal-themed, bogus bioinformatics names…that have nothing to do with animals!

Bioinformaticians make the worst zookeepers:

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

Q

R

S

T

U

V

W

X

Y

Z

 

Other suggestions welcome! Only requirements are that:

  1. The name is bogus, i.e. not a straightforward acronym and worthy of a JABBA award
  2. The acronym is named after an animal (or animal grouping)
  3. The software/tool has nothing to do with the animal in question

Great Scott! Five fun facts about DNA sequencing from 1985

As everyone is celebrating a certain 2015–themed calendar event today, I thought we could instead go back to the future past of DNA sequencing.

 

1.

Thirty years ago there were no automated sequencing machines. However, Sanger sequencing technology could still provide longer reads than most of Illumina's machines today, e.g. from this paper (A rapid procedure for DNA sequencing using transposon-promoted deletions in Escherichia coli):

The length of the sequence that could be read from each gel in a single run varied from 175 to 200 nt.

 

2.

The idea of sequencing nuclear genomes was still largely a pipe dream, but smaller genomes were tractable. 1985 saw the addition of the Xenopus laevis mitochondrial genome to the tiny collection of organelle genome sequences. Figure 3 of this paper displayed the full sequence, spread over six pages that looked like this:

Including long DNA sequences in journal articles was a surprisingly common practice at this time.

 

3.

There were two releases of GenBank in 1985. The second release saw the database grow to an astounding set of 5,700 sequences, totalling 5,204,420 bp. For comparison, this year also saw the release of the Commodore 128 home computer which came with 128 KB of RAM. The first 3.5" hard drives were only a couple of years old, and could store 10 MB (so capable of storing the DNA sequences in GenBank, but possibly not the associated annotation).

 

4.

The SEQ-ED program was published, allowing the handling of 'long DNA sequences' that were 'up to 200 Kbp'.

 

5.

Somewhat amazingly, people were writing bioinformatics software for Apple computers. The journal CABIOS included this paper:

But how did people distribute software in the days when there was no GitHub, SourceForge, or indeed…no world wide web?

For both code and source of PEGASE, please send two blank 5" diskettes and indicate precisely your system configuration (there is a slight difference between the Apple II+ and the Apple lIe version which depends on the availability of lower case characters).

BINGO, DINGO, PINGO, RINGO, and SPINGO

Dovetail takes flight [Link] →

If you ever want to know about the latest developments in sequencing, you owe it to yourself to follow Keith Robison's blog. In his latest post he talks about the launch of the new de novo assembly service from Dovetail Genomics. Keith concludes:

Personally, a pure service offering is very attractive, since that means not having to find internal resources to learn the new technology and then execute on it. I checked with Dovetail, and while I don't have $40K burning a hole in my pocket, if I did I could grab something out of the garden or from the local seafood market, I really could have a complex genome scaffold of my very own in about two months. That's an exciting vision, and perhaps will be a major force in the sunsetting of science's tolerance for highly fragmented draft genomes.

Readers may also enjoy Bio-IT World's report on this new Dovetail service.

Another survey on bioinformatics practices

I recently wrote about the bioinformatics survey that Nick Loman and Tom Connor published. Well if people are interested, there is another bioinformatics survey happening, organised by Elia Brodsky (@EliaBrodsky).

Elia works at Pine Biotech and he says that the results of the survey will be publicized on their website.

You can take the survey here and you can read more details about it on Elia's LinkedIn post: Bioinformatics - useful or just frustrating?

Another hard-to-pronounce bioinformatics software name

This was from a few months ago, published in the journal Nucleic Acids Research:

So how do you pronounce 'FunFHMMer'? I can imagine several possibilities:

  1. Fun-eff-aitch-em-em-er
  2. Fun-eff-aitch-em-mer
  3. Fun-eff-hammer
  4. Fünf-hammer

Reading the manuscript suggests that 'FunF' stems from 'FunFam(s)' which in turn is derived from 'functional families'. This would suggest that options 1 or 3 above might be the correct way to pronounce this software's name.

The fully expanded description of this web server's name becomes a bit of a mouthful:

Class Architecture Topology Homologous Superfamily Functional Families Hidden Markov Model (maker?)

We asked 272 bioinformaticians…name something that makes you angry: more reflections on the poor state of software documentation.

I'd like to share the details of a recent survey conducted by Nick Loman and Thomas Connor that tried to understand current issues with bioinformatics practice and training.

The survey was announced on twitter and attracted almost 300 responses. Nick and Tom have kindly placed the results of the survey on Figshare so that others can play with the data (it seems fitting to talk about this today as it is International Open Access Week):

When you ask a bunch of bioinformaticians the question What things most frustrate you or limit your ability to carry out bioinformatics analysis? you can be sure that you will attract some passionate, and often amusing, answers (I particularly liked someone's response to this question "Not enough Heng Li").

I was struck by how many people raised the issue of poor, incomplete, or otherwise terrible software documentation as a problem (there were at least 42 responses that mentioned this). The availability of 'good documentation' was also listed as the 2nd most important factor when choosing software to use.

I recently wrote about whether this problem is something that really needs to be dealt with by journals and by the review process. It shouldn't be enough that software is available and that it works, we should have some minimal expectation for what documentation should accompany bioinformatics software.

Keith's 10 point checklist for reviewing software

If you are ever in a position to review a software-based manuscript, please check for the following:

  1. Is there a plain text README file that accompanies the software and which explains what the program does and who created it?
  2. Is there a comprehensive manual available somewhere that describes what every option of the program does?
  3. Is there a clear version number or release date for the software?
  4. Does the software provide clear installation instructions (where relevant) that actually work?
  5. Is the software accompanied by an appropriate license?
  6. For command-line programs, does the program give some sensible output when no arguments are provided?
  7. For command-line programs, does the program give some sensible output when -h and/or --help is specified (see this old post of mine for more on this topic)?
  8. For command-line programs, does the built-in help/documentation agree with the external documentation (text/PDF), i.e. do they both list the same features/options?
  9. For script based software (Perl, Python etc.), does the code contain a reasonable level of comments that allow someone with relevant coding experience to understand what the major sections of the program are trying to do?
  10. Is there a contact email address (or link to support web page) provided so that a user can ask questions and get more help?

I'm not expecting every piece of bioinformatics software to tick all 10 of these boxes, but most of these are relatively low-hanging fruit. If you are not prepared to provide useful documentation for your software, then you should also be prepared for people to choose not to use your software, and for reviewers to reject your manuscript!

Your help needed: readers of ACGT can take part in a scientific study and win prizes

I’ve teamed up with researcher Paige Brown Jarreau (@fromthelabbench on twitter) to create a survey of ACGT readers, the results of which will be combined with feedback from readers of other science blogs.

Paige is a postdoctoral researcher at the Manship School of Mass Communication, Louisiana State University and her research focuses on the intersection of science communication, journalism, and new media. She also writes on her popular From the Lab Bench blog.

By participating in this 10–15 minute survey, you’ll be helping me improve ACGT, but more importantly you will be contributing to our understanding of science blog readership. You will also get FREE science art from Paige's Photography for participating, as well as a chance to win a t-shirt and a $50 Amazon gift card!

Click on the following link to take the survey: http://bit.ly/mysciblogreaders

Thanks!

Keith

P.S. Even if you don't take part in the survey, you should still check out Paige's amazing photography, her picture of a Western lowland gorilla is stunning.