Archive for March, 2010

International Women’s Day

Monday, March 8th, 2010

Few tragedies can be more extensive than the stunting of life, few injustices deeper than the denial of an opportunity to strive or even to hope, by a limit imposed from without, but falsely identified as lying within.

- Steven Jay Gould, The Mismeasure of Man

Today is International Women’s Day; today, we remember the all-to-quickly forgotten contributions of women to society, to industry, and to intellectual thought. It is also, importantly, a day to remember the hardships that women have had to fight through, and how far we still have to go to conquer the biases and prejudices that still exist at every level of society. In particular, I think that this should be a time for us scientists to consider how our field and our institutions have treated women, and how science can be used to hurt or help the cause of women.

Biologists have a far from untainted history when it comes to the treatment of women. The late Steven Jay Gould, in his essay Women’s Brains, documented how the fathers of anthropometry, lead by Paul Broca, used bad statistics on brain measurements to infer a general lack of intelligence in women, going on to argue against their access to higher education. Milder versions of this sort of thinking still go on today; in recent years, we’ve seen Lawrence Summers, the president of Harvard, comment that there may be a general lack of highly intelligent women compared to men, because of a (speculated) innate difference in the spread of intelligence, and that this may drive the lack of women in high-up academic positions. For better or for worse, the public still have a lot of trust for scientists, and unfounded and speculative statements such as these can do a lot to reinforce existing prejudices.

Despite dodgy patches in our past, science is far from an inherently sexist process. As Gould made clear in his take-down of Broca, the opinions the anthropometricists held were bad science; they were based on a shallow understanding of the statistics, and a failure to look at the factors that contributed to brain differences. It is bad science (fueled by unacknowledged biases) that leads people to make these statements, and ultimately it will be good data that counteracts it.

In that spirit, I have read a nice crop of blog posts over the last few months. In a series of posts collected together for Women’s Day, Ed Yong explains how the lack of female grandmasters is entirely explained by sex differences in the number of people taking up chess, that differences in maths ability is driven by gender inequality, that the ‘larger variation’ hypothesis falls down when you look across difference cultures, and that uncouncious but identifiable gender stereotypes in a society correlates strongly with sex differences in ability.

Another, unexpected source for challenging gender stereotypes is OkTrends, the datablog of the dating site OkCupid. A recent post was on “Older Women” (in this case, defined as women in their 30s and 40s); many men refuse to date women in this age range, citing beliefs that they are neurotic, non-sexual, unattractive, and too serious about relationships. However, none of these things are true; the data shows that women in their 30s and 40s are more self-confident, less sexually conservative, and less concerned about finding a relationship that leads to marriage; and while some women, with very youth-based looks, may lose their attractiveness with age, the majority (90% or more) of women look just as attractive at 40 as they did at 18. Men’s opinions on these women are not based on any actual experience of them; they are based on stereotypes about ‘older women’, which are inventions, propagating through a youth-obsessed culture.

These studies, and dozens of others, are building up an accurate picture of how society, through subtle effects of institutions, expectations and stereotypes, partition men and women into different roles; and when we know how it happens, we can attempt to counteract it.

AGBT: Speculating on Third Gen Tech

Tuesday, March 2nd, 2010

So, AGBT is over. I’ve reported on the existing tech in my previous post; one thing that I haven’t covered so far is 3rd Generation sequencing. Time to rectify this.

We have three major players, two of which had a strong presence at AGBT. Pacific Biosciences had a major launch (covered extensively elsewhere), and Life Technologies gave a surprisingly awesome presentation on their new Quantum Dot sequencing technology, QDot. Left out was Oxford Nanopore, the other major player in the 3rd Gen sphere; they did not present anything at AGBT, and I hope they all know that I am very angry about this.

We now have some information about these technologies; we know, in broad terms, how they work, and we can make some guesses about how they’ll compare. Based on the extremely limited amount of data we have at the moment, and a few speculative computer simulations (the R code for which can be read here), I’m going to draw some overall conclusions about how each tech will perform in terms of read length, yield, and accuracy.

To get a lot of this data, I’ve made “educated guesses” at the parameters (mostly based on what we know from the PacBio machine). This is an ‘all things being equal’ analysis; I assume that PacBio, Nanopore and all have the same read density, and the same enzyme efficiency; i.e. that the probability of the QDot polymerase dying is the same as for the PacBio polymerase, which are both the same as the DNA strand falling off the nanopore. If any of the companies feel like providing me with their molecule densities and decay parameters for their enzymes (ha!), I’ll happily fix the plots.

I really must repeat; all of these graphs or figures are guesses. I have no actual data beyond what has publicly been announced by the companies. I fully expect much of this to be proved wrong over the next year: this is just my guess at what the machines may look like. I should especially emphasise that I have not used any information sourced via my employer about any of these technologies.

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