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My Blank Pages V: Raw Data

Raw Data: A novel on Life in Science by Pernille Rørth (Springer, 2016)

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I was keen to read this “lab lit” novel written by renowned cell biologist Pernille Rørth. I’d seen lots of enthusiastic comments about the book, and it didn’t disappoint.

I was frustrated to read two pieces about Raw Data on Retraction Watch and The Node, both of which gave the plot away with no warning, so if you haven’t read it and want to enjoy the suspense while you read, look away now.

The story is set in a high flying cancer cell biology lab in Boston. Postdocs are working night and day to try and land a paper in Nature and to become an independent PI. Chloe manages it, while Karen is struggling, despite her best efforts. Karen accidentally uncovers that Chloe may have cut some corners to get her paper into Nature and this sets off a cascade of events, leading to the retraction of the paper. It’s a fascinating tale, well-written and completely absorbing. I recommend it for anyone working in science. You will smile at the references to conference coffee, failed scientists and more.

The plotline is highly reminiscent of Intuition by Allegra Goodman, even down to the tumours growing in the mice. Both stories echo the real-life events of Thereza Imanishi-Kari which are detailed in the overlong but comprehensive The Baltimore Case by Daniel J. Kevles. Rørth’s retelling of the science world is more convincing that Goodman’s, due in part to her 25 years as a scientist. Nonetheless, Intuition is a great book that I’d also recommend in this genre.

Raw Data is thought-provoking. You can ponder the role of Tom, the PI who has cultivated a certain atmosphere in the lab. What about the pressure to publish? How about the peer reviewers who dangle the carrot of “get this result and you can have a Nature paper” in front of Chloe? It’s a toxic mix and it’s happening in labs all over the world. A terrifying thought.

On the role of Tom: one thing that is slightly underexplored is the fact that Tom tells Chloe that there is a competing group that could ‘scoop’ her while she is rushing to finish her paper. It isn’t clear whether this group actually exists and if this was a tactic to gee her along. Either way it is another bit of pressure which goes on to create the misconduct.

Not so long ago a high profile research institute in the UK announced that it was recruiting PIs by looking for the “best scientific athlete”. I read last week that so far from the London 2012 Olympics, 37 track-and-field sportspeople have had their results disqualified by the IAAF for doping. The parallels are interesting. Science, like sport, is run with winner-takes-all rules and the high stakes and pressure that go along with it. The incentives are dangerous and I wonder what we are creating with this atmosphere. Certainly, as PIs we have a real responsibility, just as coaches do in sport, to ensure our trainees make the right choices in their career.

I’ve seen nothing but recommendations for this book so far and mine is another one.

Here’s Matthew Freeman saying that it would be required reading for everyone in his lab:

My Blank Pages is a track by Velvet Crush. This is an occasional series of book reviews.

My Blank Pages IV: Every Song Ever

Every Song Ever: Twenty Ways to Listen in an Age of Musical Plenty

Ben Ratliff (Farrar, Straus and Giroux)

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A non-science book review for today’s post. This is a great read on “how to listen to music”. There have been hundreds of books published along these lines, the innovation here however is that we now live in an age of musical plenty. Every song ever recorded is available at our fingertips to listen to when, where and how we want. This means that the author can draw on Thelonious Monk, Sunn O))), Shostakovitch and Mariah Carey. And you can seek it out and find out whatever it is that they have in common.

I got hooked in Chapter 2 (discussing slowness in music). I was reading  and thinking: he should mention Sleep’s Dopesmoker, but what are the chances? I turn the page and there it was. Then I knew that we were literally on the same page and that I would enjoy whatever it was he had to say. Isn’t confirmation bias a wonderful  thing (outside of science).

A lot of writing about music is terrible, but I love it when it is done well. As it is here. I especially like reading “under the bonnet” analysis of songs. Ian MacDonald’s Revolution In The Head (or Twilight of the Gods by Wilfred Mellers as an extreme example) springs to mind. This close analysis means you can go back and find new treasures in old songs. And this is the essence of the book.

I must admit that I have thought about trying to write similar analyses of songs on quantixed. Aside from the fact that I don’t have time, I was worried it might make me seem like Patrick Bateman discussing the merits of Huey Lewis & The News in American Psycho. It’s something that’s difficult to do well and Ratliff’s analyses here are light touch and spot-on.

The short section on blast beats which mentioned D.R.I. made me smile too. Although there’s a factual error here. Ratliff talks about how singer-drummer-brother combo Kurt and Eric Brecht lock in on Draft Me when they played CBGB’s in 1984. Drummer Eric had left the band at that point to be replaced by Felix Griffin, and it is him, not Eric, duelling with vocalist Kurt. Both on LP Dealing With It and the gig at CBGB’s which was later released as an LP and video. Again it’s a band that I have soft spot for and it was great to see them picked out.

There were a couple of quotes that I found amusing, being a CD collector and something of a completist. Here’s one:

A friend described to me the experience of acquiring a complete CD collection of Mozart, after having had a piece-by-piece relationship with his music for most of his life. It was 175 CDs, or something like that. “I realized,” he said, “that now that I had it all, I never needed to listen to it again.

Along the same lines, I thought this quote was pretty chilling.

We can pretty much wave bye-bye to the completist-music-collector impulse: it had a limited run in the human brain, probably 1930 to 2010. (It still exists in a fitful way, but it doesn’t have a consensual frame: there is no style for it.) It is not only a way of buying, owning, and arranging music-related objects and experiences in one’s life, but also a distinct way of listening.

 

As somebody who is not a fan of streaming and still values physically owning music I know I am out-of-step with the rest of the world. However I think this quote is at odds with what the whole book is trying to achieve. The guy listening to music on his phone speaker on the bus, described in the intro can’t hear and appreciate much of what is described in the book. To hear that squeak of John Bonham’s kick drum pedal on Since I’ve Been Loving You from Led Zeppelin III, you need to be listening in the old-fashioned way, rather than in the noisy and busy way most music is consumed nowadays.

It’s a great read. You can get it here.

My Blank Pages is a track by Velvet Crush. This is an occasional series of book reviews.

My Blank Pages III: The Art of Data Science

largeI recently finished reading The Art of Data Science by Roger Peng & Elizabeth Matsui. Roger, together with Jeff Leek, writes the Simply Statistics blog and he works at JHU with Elizabeth.

The aim of the book is to give a guide to data analysis. It is not meant as a comprehensive data analysis “how to”, nor is it a manual for statistics or programming. Instead it is a high-level guide: how to think about data analysis and how to go about doing it. This makes it an interesting read for anyone working with data.

I think anyone who reads the Simply Statistics blog or who has read the piece Roger and Jeff wrote for Science, will be familiar with a lot of the content in here. At the beginning of the book, I didn’t feel like I learned too much. However, I can see that the “converted” are maybe not the target audience here. Towards the end of the book, the authors walk through a few examples of how to analyse some data focussing on the question in mind, how to refine it and then how to start the analysis. This is the most useful aspect of the book in my opinion, to see the approach to data analysis working in practice. The authors sum up the book early on by comparing it to books about songwriting. I admit to rolling my eyes at this comparison (data analysis as an artform…), but actually it is a good analogy. I think many people who work with data know how to do it, in the way that people who write songs know how to do it, although they probably have not had a formal course in the techniques that are being used. Equally reading a guidebook on songwriting will not make you a great songwriter. A book can only get you so far, intuition and invention are required and the same applies to data science.

The book was published via Lean Pub who have an interesting model where you pay a recommended price (or more!) but if you don’t have the money, you can pay less. Also, you can see what fraction goes to the author(s). The books can be updated continually as typos or code updates are fixed. Roger and the Simply Stats people have put out a few books via this publisher. These books on R, programming, statistics and data science all look good and it seems more books are coming soon.

On a personal note: In 2014, I decided to try and read one book per month. I managed it, but in 2015, I am struggling. It is now November and this book is the 7th I’ve read this year. It was published in September but it took me until now to finish it. Too much going on…

My Blank Pages is a track by Velvet Crush. This is an occasional series of book reviews.

My Blank Pages II: Statistics Done Wrong

I have just finished reading this excellent book, Statistics done wrong: a woefully complete guide by Alex Reinhart. I’d recommend it to anyone interested in quantitative biology and particularly to PhD students starting out in biomedical science.

20150524_214742Statistics is a topic that many people find difficult to grasp. I think there are a couple of reasons for this that I’ll go into below. The aim of this book is to comprehensively cover the common mistakes and errors that are continually crop up in data analysis. The author writes in an easy-to-understand style and – this is the important bit – he dispenses with nearly all the equations. The result is an accessible guide on “what not to do” in significance testing.

I think there are two main reasons why people find statistics tough: uncertainty and mathematical anxiety.

First, uncertainty. What I mean is the uncertainty over what statistical approach to take, rather than the uncertainty that can be studied using statistics! It is very easy to find fault in which statistical approaches have been used in a study by a biologist. Why did they show the confidence interval and not the standard deviation? Why haven’t they corrected for multiple testing…? Statistics has a “gotcha” reputation. The reason for the uncertainty is that it is difficult to come up with a hard-and-fast set of guidelines of approaches to take, because this depends a lot on the type of data that has been collected, what is being tested etc. And there are often several ways to do the same thing. This uncertainty doesn’t go away even with a firm grounding in statistics. The methods are nearly always up for debate as far as I can see. And I think it is this uncertainty that prevents people from really engaging with statistics. In the absence of clear direction, it seems like having in mind a set of “what not to do”, is a useful approach to stats.

Second, mathematical anxiety, i.e. fear of maths. Biology has a reputation for being populated by people who ended up here through an affinity with science but a discomfort with physics and maths. This is unfair as there are many areas of biology where this is not true and statistical/quantitative approaches are right at the forefront. Nonetheless, there is a reason why there are umpteen “Statistics for Biologists” books in the bookshop. Now, the way that statistics is taught is to crunch through the equations that describe statistical concepts. Again, this means that people who really need to know about statistics for their research are held back if they don’t have a mathematical background or just find maths a bit daunting. The situation is well described by a recent post at Will Kurt’s excellent Count Bayesie blog on the teaching of statistics. His point is: insisting that students know these equations gets in the way of them understanding statistics. Nowadays, calculating something like the standard deviation is trivial using a computer and we are unlikely to need to know the derivation of an equation in order to do our work. We should just skip the equations and explain why.

The nice thing about this book is that the author has collected together all the faux pas that you’re likely to encounter and how to avoid them. This goes some way to addressing uncertainty in what methods to use. Secondly, the author has dispensed with the equations, so the mathematically anxious can pick it up without fear. These features make this book different to other stats books that I’ve read.

You can find copies at many online retailers. It’s published by No Starch. I picked up a copy after reading about it on Nathan Yau’s Flowing Data blog.

The post title comes from “My Blank Pages” by Velvet Crush from their Teenage Symphonies to God LP.