Mailund on the Internet

From my own experience I know that it can be hard to get access to data that you would really love to analyse, but I didn’t expect it to be quite this bad, even for data that is required to be available by the journals where the papers describing the data are published:

Empirical study of data sharing by authors publishing in PLoS journals

Savage and Vickers, PLoS ONE 2009

Background

Many journals now require authors share their data with other investigators, either by depositing the data in a public repository or making it freely available upon request. These policies are explicit, but remain largely untested. We sought to determine how well authors comply with such policies by requesting data from authors who had published in one of two journals with clear data sharing policies.

Methods and Findings

We requested data from ten investigators who had published in either PLoS Medicine or PLoS Clinical Trials. All responses were carefully documented. In the event that we were refused data, we reminded authors of the journal’s data sharing guidelines. If we did not receive a response to our initial request, a second request was made. Following the ten requests for raw data, three investigators did not respond, four authors responded and refused to share their data, two email addresses were no longer valid, and one author requested further details. A reminder of PLoS’s explicit requirement that authors share data did not change the reply from the four authors who initially refused. Only one author sent an original data set.

Conclusions

We received only one of ten raw data sets requested. This suggests that journal policies requiring data sharing do not lead to authors making their data sets available to independent investigators.

Getting a 10% success rate, when it should be 100% is pretty bad…
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I read this paper on our way back from Leipzig and then again today to see if I missed anything in the first read through (I was pretty tired at the time).

Detecting ancient admixture and estimating demographic parameters in multiple human populations

Wall, Lohmueller and Plagnol, Mol Biol Evo 26(8):1823-1827

We analyze patterns of genetic variation in extant human polymorphism data from the National Institute of Environmental Health Sciences single nucleotide polymorphism project to estimate human demographic parameters. We update our previous work by considering a larger data set (more genes and more populations) and by explicitly estimating the amount of putative admixture between modern humans and archaic human groups (e.g., Neandertals, Homo erectus, and Homo floresiensis). We find evidence for this ancient admixture in European, East Asian, and West African samples, suggesting that admixture between diverged hominin groups may be a general feature of recent human evolution.

What they do in this paper is to fit a two population coalescent model, with expansion, migration, bottlenecks and the works, to both an African+European and an African+Asian data set, then use this fitted model as a null model of the genetics of the populations.  They then 1) do a test on an LD statistic against this null model, taking rejections of this null model as evidence for admixture from archaic humans, and 2) fit an admixture extension of the model to estimate the level of admixture.  They find evidence for admixture with archaic humans for both data sets, with a somewhat higher degree in the Europeans.

I’m a bit underwhelmed by the paper, I must admit.  I’m not saying that there is no admixture with archaic humans, but this approach does not convince me.

Even when taking various demographic effects into account in the modeling, the null model is unlikely to exactly fit real data.  Taking deviations from the null model as any kind of evidence for admixture thus seems a bit hasty.

Not that I have any better ideas as to how to approach this, just, in my eyes the jury is still out on the question of admixture with archaic humans…

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Wall, J., Lohmueller, K., & Plagnol, V. (2009). Detecting Ancient Admixture and Estimating Demographic Parameters in Multiple Human Populations Molecular Biology and Evolution, 26 (8), 1823-1827 DOI: 10.1093/molbev/msp096
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As you might have heard, the PLoS journals have added access statistics to their papers, so you can see how often a given paper is accessed, either the html page or PDF downloads and whatnot.

Narcissistic as I am, I checked our CoalHMM PLoS Genetics paper.

I don’t know what I expected, but 15 thousand views is probably more than I did expect.  Not all of those are people who actually read the paper, of course, but the two thousand PDF downloads might be, and that is a lot of people…

I can just hope they liked it.

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