Is there an alternative to ‘Excel is the devil’?

In my last post I shared the slides for my talk  “5 selfish reasons to work reproducibly”.

In my talk I stressed the importance of using scripts and code to make analyses reproducible. Instead of clicking, cutting and pasting as you would have to do in a tool like Excel.

I had also submitted my slides to the F1000 slides collection and after a few days got a very polite email back, asking me to rethink the keywords I had chosen in the submission:

Thank you for your slides submission: “5 selfish reasons to work reproducibly”.

Just a quick note to say that keywords are displayed alongside your presentation and are often how users will find your submission, by searching our site.

With this in mind, we were wondering if you had an alternative to “Excel is the devil” which might be more likely to appear on search results. [my emphasis]

First of all, I am impressed by how serious they take curating slides at F1000.

And, yeah, I might come up with some other keywords, even though I think ‘Excel is the devil’ remains quite accurate.

You can find the slides together with the new keywords (quite boring: Reproducible research, knitr, Sweave, Successful lab, Career advice) here:

Markowetz F.
Five selfish reasons to work reproducibly [v1; not peer reviewed].
F1000Research 2015, 4:207 (slide presentation)
(doi: 10.7490/f1000research.1000179.1)



Five selfish reasons for working reproducibly

And so, my fellow scientists: Ask not what you can do for reproducibility — ask what reproducibility can do for you!

The following is a summary of a talk I gave in my institute and at the Gurdon in Cambridge. My job was to motivate why working reproducibly is a good strategy for ambitious scientists. Right after my talk, Gordon Brown (CRUK CI) and Stephen Eglen (Cambridge DAMTP)  presented tools and case studies of reproducible work.

All materials are on github and below are my slides, thanks to slideshare:

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Slides for my ISMB network SIG keynote

Wohoo! My first set of citable slides.

I submitted the talk I gave at the ISMB 2015 network SIG to F1000. And they made it citable:

Markowetz F.
Functional analysis of interaction networks [v1; not peer reviewed].
F1000Research 2015, 4:221 (slide presentation)
(doi: 10.7490/f1000research.1000198.1)

To make sure that the animations are all visible I duplicated some slides several times and because they contain network plots the file is a massive 43 MB. I need to think of a better way to do this next time …


Books, Science

New Book! SYSTEMS GENETICS by Markowetz and Boutros at Cambridge University Press

The book on Systems Genetics I have edited with Michael Boutros just came out! Wohoo!

You can get a look at the first copies at ISMB this year and I will shamelessly promote it in my talk at the Networks SIG on July 10th.

You can download the first introductory chapter written by Michael and me here.

Here is the promo text for your pleasure and enjoyment:

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Duty Calls, Science

“Superstar professors with massive research groups are bad for science.” I agree.

‘My professor demands to be listed as an author on many of my papers’ writes an anonymous scientist in the Guardian.

[T]here’s one instance where it’s acceptable for scientists to lie: when fraudulently claiming authorship of a paper.

Too often, researchers attach their names to reports when they have contributed nothing at all to the work.

The problem gets worse the higher up the academic ladder you go.

I think this is completely true.

The reasons are manifold:

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At the movies: “My career in genomics: evolution “

Former postdoc Roland Schwarz of MEDICC fame has become a movie star.
Or at least the face of computational biology for the Wellcome Genome Campus:

In this film Roland Schwarz talks about his research using computers to model and understand evolution. This is one of a series of films providing a unique insight into different careers in the field of genomics.

Go here or watch it directly:


Career, Science

Forget about your animal friends – how to draft a recommendation letter

Marcia McNutt, Editor-in-Chief of Science, wrote a thoughtful Editorial about recommendation letters:

I noted an overall bias in the language used to describe the male candidates versus some of the female candidates. In some letters, women were described as “friendly,” “kind,” “pleasant,” “humble,” and frequently, “nice.”

[O]ne letter described how the candidate was so good to her elderly mother, yet still enjoyed life, spending time in nature with her husband and her animal friends.

Another letter reflected amazement that the candidate managed to balance so efficiently being a student, a scientist, and a mother.

But isn’t it good being nice, humble and having lots of animal friends?

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A unifying theory of cancer evolution: genomes in context

Finally a review article on cancer evolution that I really enjoyed. Maybe because it’s not a Review but an Opinion piece: “Evolutionary dynamics of carcinogenesis and why targeted therapy does not work” by Gillies, Verduzco and Gatenby (GVG for short).

Extra brownie points for a provocative title.

The first publication on tumor heterogeneity

First of all, GVG extended my knowledge of the history of tumor heterogeneity by citing a paper from 1930:

Ö. Winge, Zytologische Untersuchungen über die Natur maligner Tumoren, Zeitschrift für Zellforschung und Mikroskopische Anatomie, 6. JUNI 1930, Volume 10, Issue 4, pp 683-735,

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Evolution in cancer: Yes! Darwin: No?

Series on Tumor Evolution
Evolution is a fancy word for gradual change. In this general sense, all kinds of things evolve. The universe evolves, societies evolve, finches evolve.

The mechanisms and principles of these three evolutions are all different. For example, the finches change by Darwinian evolution, which is one particular type of evolution based on natural selection: There is diversity in traits between individuals in a population; because of their traits some individuals have more offspring than others; the traits are heritable and can be passed on to offspring. Over time the favorable traits will become dominant in the population – and with them the genotypes underlying them.

This is how it works for finches. How about cancer? Is that developing by Darwinian evolution too? Not so fast, say Sidow and Spies:

The forced application of terms and concepts from organismal population genetics can distract from the fundamental simplicity of cancer evolution,

write Sidow and Spies in their review ‘Concepts in solid tumor evolution‘ (TiG 2015) and they plan to set the record straight.

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Hypnotizing the reader into accepting the authors’ conclusions

I just had a quick look at last week’s Nature Genetics Editorial Cause, correlation, conjecture.

[W]e have been struck again by the amount of repetition of claims and arguments in most research articles.

The main claims of the paper are detailed in the title, abstract, introduction, results, figures and discussion as well as in the methods as if to hypnotize the reader into accepting the authors’ conclusions. [My emphasis]

Repetitiveness shows lack of confidence. One more reason to remove it.

And the Nat Gen editors even mention a tool to better structure a paper:

Our recommendation in planning a research paper is to lay out the claims together with the supporting evidence and methods in a three-column table. The rows follow one another logically as one experiment or analysis follows necessarily from its predecessor.

It is unfortunate that the short article doesn’t contain an example of such a table. But I like the idea and might just try it next time we write a paper.


Cause, correlation, conjecture. Nature Genetics 47, 305(2015) doi:10.1038/ng.3271

Creativity, Science

Healing Art of Pathology

Over at Connecting the dots … Jakob Scott describes an art (and book) project involving histology slides:

A project he began, called My Sarcoma, during which Ray painted over the top of his OWN histology images, transformed Ray from a sick and dying patient back into a living and vibrant artist.


An example of collaborative art:

Each of the paintings that Ray has made during this journey has had more than just Ray’s hands involved. Indeed, to make the paintings as you see them, a surgeon had to cut out his tumor, a pathologist had to stain and mount the tissue and a screen printer had to prepare the canvas.




Inferring tumour evolution 6 – What do we talk about when we talk about a clone?

Series on Tumor Evolution

What do you picture when you hear the word ‘clone’? A white-clad imperial stormtrooper from Star Wars: Attack of the clones? Or a fluffy sheep called Dolly? Both are good choices. Both are good, solid, well understood clones. But how is the situation in cancer? This is where it gets difficult. In most talks (at least the ones I sit in) the word ‘clone’ is used very loosely like it was a trivial concept. My goal for today is to show that reality is more complex than the ‘plain vanilla’ version that is often described on some introductory slide.

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Books, Science

Steven Weinberg and the smugness of hindsight

One of the more helpful pieces of advice I recommend to new starters in my team are Steven Weinberg’s “Four golden lessons“. Weinberg is a physics Nobel laureate and “considered by many to be the preeminent theoretical physicist alive in the world today” (says Wikipedia). I guess this means he knows his physics … and his four golden lessons certainly are helpful:

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How normal is normal? Surprising mutations in normal-looking prostate tissue

Series on Tumor Evolution

“Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue,” is the title of another recent paper that caught my attention.

I like long titles, because they often already contain the full story without the bothersome detail of the rest of the paper. Let’s look at the pieces of this one; two things stand out:

First of all, prostate cancer is generally multifocal, which means that cancer develops in different regions of the prostate, and the authors have found independent clonal expansions for these different foci. So it is not that the cancer started in one spot and then spread, these different tumors in the prostate developed independently from each other.

Morphologically normal is not always genetically normal

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