Illumina's new NovaSeq platform unveiled at The Institute of Cancer Research, London →

Dr Nik Matthews, Genomics Manager in the ICR's Tumour Profiling Unit. Credit: ICR

Dr Nik Matthews, Genomics Manager in the ICR's Tumour Profiling Unit. Credit: ICR

It feels a bit strange to be using this blog to link to a news post at my current employer, but I'm happy to share the news that the ICR has become the first organisation in the UK to deploy Illumina's NovaSeq platform.

The ICR's Dr Chris Lord, Deputy Director of the Breast Cancer Now Research Centre, had this to say:

One key area we are keen to use the NovaSeq sequencer for is to discover new ways to select the best available treatment for each individual cancer patient’s specific disease.

If we can do this, we should be able to improve how a significant number of patients are treated. With the NovaSeq system, this kind of work is now feasible – this will be a real game-changer for a lot of the work across the ICR.

Read more in the full news article on the ICR website:

Chromosome-Scale Scaffolds And The State of Genome Assembly →

Keith Robison has written another fantastic post on his Omics! Omics! blog which is a great read for two reasons.

First he looks at the issues regarding chromosome-size scaffolds that can now be produced with Hi-C sequencing approches. He then goes on to provide a brilliant overview of what the latest sequencing and mapping technologies mean for the field of genome assembly:

For high quality de novo genomes, the technology options appear to be converging for the moment on five basic technologies which can be mixed-and-matched.

  • Hi-C (in vitro or in vivo)
  • Rapid Physical Maps (BioNano Genomics)
  • Linked Reads (10X, iGenomX)
  • Oxford Nanopore
  • Pacific Biosciences
  • vanilla Illumina paired end

This second section should be required reading for anyone interested in genome assembly, particularly if you've been away for the field for a while.

Read the post: Chromosome-Scale Scaffolds And The State of Genome Assembly

What did I learn at the Festival of Genomics conference? →

Last week I attended the excellent Festival of Genomics conference in London, organised by Front Line Genomics. This was the first time I had been to a conference as a communications person rather than as a scientist…something that felt quite strange.

In addition to live-tweeting many talks for The Institute of Cancer Research where I work, I also recorded some videos of ICR scientists on the conference floor. All were asked to respond to the same simple question: Why is genomics important for cancer research?. You can see the video responses on the ICR's YouTube channel.

I also made a very short video to highlight one unusual aspect of the conference…the talks were pretty much silent. Wireless headphones worn by all audience members meant that there was no need to amplify the speakers…and therefore no need for the four different 'lecture theatres' to actually have any walls!

 

My first ICR blog post!

My final task was to write a blog post about some aspect of the conference. Before the conference started, I thought I might write something that was more focused on genomics technologies. However, I was surprised by how much of the conference covered genomics as part of healthcare.

In particular, I was left with the sense that genomics is finally delivering on some of the promises made back in 2003 when the human genome sequence was published. One of the target areas that was mentioned in this 2003 NIH press release was 'New methods for the early detection of disease'.

This is something that is now possible with whole genome sequencing being deployed as part of the 100,000 genomes project (undertaken by Genomics England). The ability to screen a patient for all known genetic diseases leads to many concerns and challenges — you should see Gattaca if you haven't already done so — but it was heartening to see how much groundwork has been put in to stay on top of some of these issues.

This is my first proper blog post for the ICR, and if you are interested in finding out more, please read my post on the ICR's Science Talk blog:

We have not yet reached 'peak CEGMA': record number of citations in 2016

Over the last few weeks, I've been closely watching the number of citations to our original 2007 CEGMA paper. Despite making it very clear on the CEGMA webpage that is has been 'discontinued' and despite leaving a comment in PubMed Commons that people should consider alternative tools, citations continue to rise.

This week we passed a milestone with the paper getting more citations in 2016 than in 2015. As the paper's Google Scholar page clearly shows, the citations have increased year-on-year ever since it was published:

While it is somewhat flattering to see research that I was involved so highly cited — I can't imagine that many papers show this pattern of citation growth over such a long period — I really hope that 2016 marks 'peak CEGMA'.

CEGMA development started in 2005, a year that pre-dates technologies such as Solexa sequencing! People should really stop using this tool and try using something like BUSCO instead.

Assembling a twitter following: people continue to be interested in genome assembly

Late in 2010, I was asked to help organise what would initially become The Assemblathon and then more formally Assemblathon 1. One of the very first things I did was to come up with the name itself — more here on naming bioinformatics projects — register the domain name, and secure the Twitter account @Assemblathon.

The original goal was to use the website and Twitter account to promote the contest and then share details of how the competition was unfolding. This is exactly what we did, all the way through to the publication of the Assemblathon 1 paper in late 2011. Around this time it seemed to make sense to also use the Twitter account to promote anything else related to the field of genome assembly and that is exactly what I did.

As well as tweeting a lot about Assemblathon 2 and a little bit about the aborted but oh-so-close-to-launching Assemblathon 3, I have found time to tweet (and retweet) several thousand links to many relevant publications and software tools.

It seems that people are finding this useful as the account keeps gaining a steady trickle of followers. The graph below shows data from when I started tracking the follower growth in early 2014:

All of which leaves me to make two concluding remarks:

  1. There can be tremendous utility in having an outlet — such as a Twitter account — to focus on a very niche subject (maybe some would say that genome assembly is no longer a niche field?).
  2. Although I am no longer working on the Assemblathon projects — I'm not even a researcher any more — I'm happy to keep posting to this account as long as people find it useful.

101 questions with a bioinformatician #38: Gene Myers

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.

Gene Myers is a Director at the Max-Planck Institute for Molecular Cell Biology
and Genetics (MPI-CBG) and the Klaus-Tschiar Chair of the Center for Systems Biology Dresden (CSBD).

Maybe you've heard of Gene for his pivotal role in developing the Celera genome assembler which led to genome assemblies for mouse, human, and drosophila (the first whole genome shotgun assembly of a multicellular organism). You may also know Gene from his work in helping develop a fairly obscure bioinformatics tool that no-one uses (just the 58,000 citations in Google Scholar).

His current research focuses on developing new methods for microscopy and image analysis; from his research page:

"The overarching goal of our group is to build optical devices, collect molecular reagents, and develop analysis software to monitor in as much detail as possible the concentration and localization of proteins, transcripts, and other entities of interest within a developing cohort of cells for the purpose of [developing] a biophysical understanding of development at the level of cell communication and force generation."

You can find out more about Gene by visiting his research page on the MPI-CBG website or by following him on Twitter (@TheGeneMyers). Finally, if you are interested in genome assembly then you may also want to check out his dazzlerblog ('The Dresden AZZembLER for long read DNA projects'). And now, on to the 101 questions...



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

The underlying technology is always changing and presenting new challenges, and the field is still evolving and becoming more "sophisticated". That is, there are still cool unsolved problems to explore despite the fact that some core aspects of the field, now in its middle-age in my view, are "overworked".



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

I'm really bored with networks and -omics. Stamp collecting large parts lists seems to have become the norm despite the fact that it rarely leads to much mechanistic insight. Without an understanding of spatial organization and soft-matter physics, most important biological phenomenon cannot be explained (e.g. AP axis orientation at the outset of worm embryogenesis).

Additionally, I was disgusted with the short-read DNA sequencers that, while cheap, produce truly miserable reconstructions of novel genomes. Good only for resequencing and digital gene expression/transcriptomics. Thank God for the recent emergence of the long-read machines.



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?

At age 18 its not so much about career specifics but one's general approach to education. For myself, I would have said, "go to class knuckle head and learn something from all the great researchers that are your teachers (instead of hanging out in your dorm room reading text books)", and for general advice to all at that stage I would say, learn mathematics and programming now while your mind is young and supple, you can acquire a large corpus of knowledge about biological processes later.



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

I don't use bioinformatics software, I make it :-) My favorite problem, yet fully solved in my opinion, is DNA sequence assembly -- it is a combinatorially very rich string problem.



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?

N — as it encompasses all the rest :-)

How would you describe genomics without using any scientific jargon?

Yesterday was the Annual Student Conference at The Institute of Cancer Research, London. As part of the ICR's Communications team, we helped run a session about the myriad ways that science can (and should) be communicated more effectively.

During this session my colleague Rob Dawson (@BioSciFan on Twitter) introduced a fun tool called the The Up-Goer Five Text Editor. This tool lets you edit text…but only by using the 1,000 most common words in the English language.

It was inspired by an XKCD comic which used the same approach to try to explain how an Apollo moon rocket works. Using this tool really makes you appreciate that just about every scientific word you might use is not on the list. So it is a good way of making you think about how to communicate science to a lay audience, completely free of jargon.

I thought I would have a go at explaining genomics. I couldn't even use the words 'science', 'machine', or 'blueprint' (let alone 'gene', 'DNA', or 'molecule'). Here is my attempt:

In every cell of our bodies, there is a written plan that explains how that cell should make all of the things that it needs to make. A cell that grows hair is very different to a cell that is in your heart or brain. However, all cells still have the same plan but different parts of the plan are turned on in different cells.

We first understood what the full plan looks like for humans in 2003. We can use computers  to make sense of the plan and to learn more about how many parts are needed to make a human (about 20,000). The better we understand the plan, the more we might be able to make human lives better.

You can edit my version online but I encourage people to try explaining your own field of work using this tool.