1) The rights reserved by the University are too limited. Rather than granting UC the right to redistribute the article, the policy should place all scholarly works produced by UC faculty under a Creative Commons Attribution License.

2) There should be no “opt-out” provision.

Here is my edited version of the proposal (my additions are in green):

The Faculty of The University of California is committed to disseminating its research and scholarship as widely as possible. In keeping with that commitment, the Faculty adopts the following policy:

Each Faculty member grants to The University of California permission to make available his or her scholarly articles and to exercise the copyright in those articles.

More specifically, each Faculty member grants to The California Digital Library, acting on behalf of the Regents of the University of California, a nonexclusive,  irrevocable, worldwide license to exercise any and all rights under copyright relating to each of his or her scholarly articles, in any medium, provided that the articles are not sold for a profit, and to authorize others to do the same.

Each Faculty member will provide a copy of each of their scholarly articles, in any medium, to  The California Digital Library, acting on behalf of the Regents of the University of California, who will make these articles available under a Creative Commons Attribution License that grants any users the right to redistribute and reuse the work provided that proper credit for its authorship is retained.

The policy applies to all scholarly articles authored or co-authored while the person is a member of the Faculty except for any articles completed before the adoption of this policy and any articles for which the Faculty member entered into an incompatible licensing or assignment agreement before the adoption of this policy.

Following adoption of this policy, faculty will not enter into any agreement with any third party that limits their ability to comply with this policy.

The University of California will waive application of the license for a particular article or delay access for a specified period of time upon express direction by a Faculty member.

Each Faculty member will provide an electronic copy of the author’s final version of each article no later than the date of its publication at no charge to the California Digital Library, or its successors, in an appropriate format. The California Digital Library, or its successors, may will make the article available in an open access repository immediately upon, or, with author consent, prior to its formal publication.

The California Digital Library, or its successors, will be responsible for interpreting this policy, resolving disputes concerning its interpretation and application, and recommending changes to the Faculty from time to time.

The policy will be reviewed after three years and a report presented to the Faculty.

Of course getting the faculty to agree to this would be great, but there is a greater need to get the administration to engage in the issue of how the work of its faculty should be communicated – something on which they, like virtually all other universities, have a very poor track record.

Would that it were so. Rather than being a watershed event in the movement to reform scholarly publishing, the tepidness of the committee’s recommendations, and the silence of the university’s administration, are just the latest manifestation of the toothless response of American universities to the “serials crisis” that has plagued libraries for decades.

Had the leaders major research universities attacked this issue head on when the deep economic flaws in system became apparent, or if they’d showed even an ounce of spine in the ensuing twenty or so years, the subscription-based model that is the root of the problem would have long ago been eliminated. The solutions have always been clear. Universities should have stopped paying for subscriptions, forcing publishers to adopt alternative economic models. And they should have started to reshape the criteria for hiring, promotion and tenure, so that current and aspiring faculty did not feel compelled to publish in journals that were bankrupting the system. But they did neither, choosing instead to let the problem fester. And even as cries from the library community intensify, our universities continue to shovel billions of dollars a year to publishers while they repeatedly fail to take the simple steps that could fix the problem overnight.

The roots of the serials crisis 

Virtually all of the problems in scholarly publishing stem from the simple act, repeated millions of times a year, of a scholar signing over copyright in their work to the journal in which their work is to appear. When they do this they hand publishers a weapon that enables them to extract almost unlimited amounts of money from libraries at the same research institutions that produced the work in the first place.

The problem arises because research libraries are charged with obtaining for scholars at their institution access to the entire scholarly output of their colleagues. Not just the most important stuff. Not just the most interesting stuff. Not just the most affordable stuff. ALL OF IT. And publishers know this. So they raise prices on their existing journals. And they launch new titles. And then they raise their prices.

What can libraries do? They have to subscribe to these journals. Their clientele wants them – indeed, they need them to do their work. They can’t cancel their subscription to Journal X in favor of the cheaper Journal Y, because the contents of X are only available in X. Every publisher is a monopoly selling an essential commodity. No wonder things have gotten out of control.

And out of control they are. Expenditures on scholarly journals at American research libraries quadrupled from 1986 to 2005, increasing at over three times the rate of inflation. This despite a massive reduction in costs due to a major shift towards electronic dissemination. These rates of growth continue nearly unabated, even in a terrible economy. (For those interested in more details, I point you to SPARC, the Scholarly Publishing and Academic Resources Coalition, who tracks journal pricing and revenues).

The opportunity universities missed

Just as the serials crisis was hitting its stride in the mid-1990′s, fate handed universities an out – the internet. In the early 1990′s access to the scholarly literature almost always occurred via print journals. By the end of the decade, virtually all scholarly journals were publishing online.

This radical transformation in how scholarly works were disseminated should have been accompanied by a corresponding radical shift in the economics of journal publishing. But it barely made a dent. Publishers, who were now primarily shipping electrons instead of ink on paper, kept raising their subscription prices as if nothing had happened. And universities let them get away with it.

By failing to show even a hint of creativity or initiative in seizing the opportunity presented by the internet to reshape the system of scholarly communication in a productive way, the leaders of American universities condemned themselves to 15 more years (and counting) of rising costs, and decreasing value. Their inaction also cost them the chance to reclaim the primary role they once held (through their university presses) in communicating the output of their scholars.

But while universities did next to nothing to fix scholarly publishing, others leapt into the fray. A new economic model, which came to be known as “open access“, emerged as an alternative to the subscription journals. Under open access the costs of publishing would be bourn up front by research sponsors, with the finished product freely available to all. In addition to the obvious good greatly expanding the reach of the scholarly literature, open access was largely free of the economic inefficiencies that created the serials crisis in the first place, and enjoyed very strong support from university libraries across the country. But despite its manifold advantages, universities as a whole did little to help it succeed.

The unholy alliance between journals and universities

The biggest obstacle to the rise of open access journals was (and to a large extent still is) the major role that journal titles play in how universities evaluate candidates for jobs and promotions. In most academic disciplines, careers are built by publishing papers in prestigious journals – those that are the most selective, and therefore have the most cache. Scholars rising through the ranks of graduate school, the job market, assistant professorships and tenure face a nearly contant barrage of messages telling them that they have to publish in the best journals if they want to succeed at the next step. Never mind that it is far less true than people believe. That people believe it is all that matters.

Almost everyone I know thinks that simply looking at journal titles is a stupid way to decide who is or is not a good researcher, and yet it remains. There are many reasons why this system persists, but the most important is that universities like it. Administrators love having something like an objective standard that can be applied to all of the candidates for a job, promotion, etc… that might allow them to compare not only candidates for one job to each other, but all candidates for any honor across the university. This is perhaps why no university that I know of has taken a forceful stand against the use of journal titles as a major factor in hiring and promotion decisions. And it is, I believe, a major reason why they are unwilling to cut off the flow of money to these journals.

It’s never too late

Although their record is pretty bad, universities could still play a major role in making scholarly publishing work better – and save themselves money in the process – with two simple actions:

• Stop the flow of money to subscription journals. Universities should not renew ANY subscriptions. They should, instead, approach them with a new deal – they’ll maintain payments at current levels for 3 more years if the journal(s) commit to being fully open access at the end of that time.
• Introduce – and heavily promote – new criteria for hiring and promotion that actively discourage the use of journal titles in evaluating candidates.

These ideas are not new. Indeed, the basic outlines appear in a fantastic essay from the Association of Research Librarians published in March 1998, describing the serials crisis and their solutions to fix it:

The question inevitably asked is, “Who goes first?” Which major universities and which scholarly societies have the will, confidence, and financial resources to get the process started?

Our answer is simple and to the point. It is time for the presidents of the nation’s major research universities to fish or cut bait. Collectively, they have both opportunity and motive—and, in the Association of American Universities, they have an organization with the capacity to convene the necessary negotiations.

It’s amazing that essentially nobody took them up on the challenge the first time. Let’s hope it doesn’t take  another 15 years.

major periodical subscriptions, especially to electronic journals published by historically key providers, cannot be sustained: continuing these subscriptions on their current footing is financially untenable

Judging from many of the responses, people seem to think this is some kind of major turning point in the push for universal open access. And the fact that even Harvard, with its billions dollar endowment, is feeling the sting of rising journal prices does seem to have struck a chord.

But librarians have been warning about the “serials crisis” for years (see, for example, this prescient 1998 report from the Association of Research Libraries, the Association of American Universities, and the Pew Higher Education Roundtable). I’ve seen dozens of letters to faculty from librarians urging them to abandon subscription journals. But they have little effect. I think this is at least in part due to the mismatch between the strength of their argument, and the weakness of their proposed solutions – a pattern repeated in the Harvard letter.

So I thought I would try to help by editing the provided list of things to consider demands:

Since the Library now must change its subscriptions and since faculty and graduate students are chief users, please consider immediately implement the following options open to faculty and students (F) and the Library (L), state other options you think viable, and communicate your views:

1. Make sure that all of your own papers are accessible by submitting them to DASH in accordance with the faculty-initiated open-access policies (F). [NOTE: Harvard's open access policy provides an opt-out provision for faculty - this is not acceptable]

2. Consider submitting Submit all of your articles to open-access journals, or to ones that have reasonable, sustainable subscription costs; move prestige to open access (F).

3. If on the editorial board of a journal involved, determine if it can be published as open access material, or independently from publishers that practice pricing described above. If not, consider resigning resign (F).

4. Contact professional organizations to raise these issues demand that they immediately support universal open access (F).

5. Encourage Demand that professional associations to take control of scholarly literature in their field or shift the management of their e-journals to library-friendly organizations (F).

6. Encourage colleagues to consider and to discuss these or other options Tell your colleagues to stop being wimps (F).

7. Sign contracts that unbundle subscriptions and concentrate on higher-use journals Do not sign any contracts to access subscription-only journals (L).

8. Immediately move all journals to a sustainable pay per use system, open access model (L).

9. Insist on subscription contracts in which the terms can be made public (L).

10. Require that all works produced by university faculty be distributed under a Creative Commons Attribution License, no matter where they are published. 

So you can imagine how thrilled she was when, as we checked the scores at mlb.com, news of the latest Red Sox debacle was followed by an add featuring R2D2 and C-3PO and the new Kinect Star Wars for the Xbox 360. She was literally jumping up and down with excitement.

And then she got a puzzled look on her face as she slowly read the text, written in big, gold, Star Wars font.

“Daddy, what’s an ‘ultimate fatherson sweepstakes’?”

I didn’t answer immediately. I was dumbfounded, and was sure I must have been reading it wrong. There was no way Major League Baseball, who have made a serious effort to reach out to their female fans, would slap my daughter in the face this way. But it said what it said. ULTIMATE FATHER-SON SWEEPSTAKES.

So I explained it to her. And she began to cry. “Why,” she asked through her tears, “is it only for boys? I like baseball too.”

Like most girls her age, she’d had boys in her first grade tell her she couldn’t do things because she wasn’t a boy. But this was literally the first time in her life that the adult world was telling her that loving sports was not for girls. It helped a little that the fine print made it clear that the contest was not actually restricted to men and boys. But she was still confused and upset.

And she wasn’t ready to let it go. She asked me about it again on our way to school this morning. What could I do but explain that a lot of people think that sports like baseball are for boys.

“But, they’re not right” she half asserted and half asked.

“No,” I said. “Don’t listen to them. They’re wrong.”

“You mean like the white people were wrong not to let Rosa Parks sit in the front of the bus?”

(She just finished a “heroes” report on Rosa Parks, and reads a book about her to her younger sister every night.)

“Yes. It’s kind of like that.”

“But I thought those people were dead.”

I didn’t know what to say.

The statement that so offended me, from the lead author of the paper, was that he was 99.9999% sure that a gene identified in his study plays a role in causing in autism. It’s a ridiculous assertion, completely at odds with what his group says in the paper. It  needs to be corrected.

However, my original post also included some statistical analyses that were based on a cursory reading their work, and, as a result, didn’t directly speak to the central claims of the paper. My basic critique is unchanged – the 99.9999% claim is insupportable – but this got me interested in the fine details of their results and analysis, and I thought it would be useful to post my thoughts here.

Let me also say at the outset that, while I didn’t like what was said in the NYT, and don’t agree with everything the authors say in the paper, I am not trying to take them to task here. Analyzing this kind of data is difficult, and there are all sorts of complexities to deal with.

First, a summary of what they did and found. The core data are sequences of the “exomes” (essentially the protein-coding portion of the genome) from 238 children with autism spectrum disorders (ASD), both of their unaffected parents, and (in 200 cases) an unaffected sibling.

The analyses they present focus on the families with data for unaffected siblings, enabling them to compare the transmission of inherited variants (those present in the parents) and de novo mutations (those not present in the parents) between affected and unaffected siblings. They observed no differences in the transmission of inherited variants between affected and unaffected individuals, but found a significant increase in the number of de novo mutations that change proteins in affected individuals. Specifically, there were 125 do novo, protein altering (mis-sense, nonsense or splicing) mutations in affected individuals compared to 87 in siblings, a significant difference (p=.01).

This observation provides reasonable support for the hypothesis that de novo mutations are associated with autism. But it does not indicate which – if any – of these specific mutations is involved. After all, that there were 87 de novo protein-altering mutations in unaffected siblings suggests that many of those identified in autistic individuals are not involved in the disease. There is also the possibility that the elevated mutations rate is a secondary consequence of some other factor that leads to autism, and that none of these specific mutations are actually directly involved in the disease.

Given that the the observation of a de novo mutation in one gene in one affected individual conveys limited information about its involvement in autism, the authors focus on cases where independent mutations were observed in the same gene in different affected individuals. The reasoning is that such an observation would be unlikely to occur by chance in a gene that is not involved in ASD.

This is where I initially mistook what they did. I assumed the quote in the NYT story was referring to the chances of observing the same gene twice amongst the 125 de novo mutations in affected individuals, and pointed out that we actually expect this to happen at least 30% of the time (I say at least because the 30% number comes from assuming random mutations are equally likely to occur in all genes – which is not correct for reasons such as differences in gene size, GC content, etc… – all things the authors factor into their calculations). Indeed, the observation in the paper that two genes are hit twice in the set of 125 is not a statistically significant finding, and, by itself would offer no evidence that these genes are involved in ASD – and the authors do not assert that it does.

Instead the authors focused on a small subset of mutations – those that introduce a premature stop codon into a gene (thereby generating a truncated protein, or, because of a process known as non-sense mediated decay, likely decrease the expression level) or alter a splice site (potentially affecting the structure of the gene). The numbers here are a lot smaller. In the affected individuals there were ten nonsense and five splicing mutations, while there were only five nonsense and no splicing mutations in the unaffected siblings. And, crucially, in the set of 15 such mutations one gene – SCN2A – appeared twice.

So now the question is, is this a significant observation? Under the simplest of models, if you picked genes 15 times randomly from a set of 21,000 you’d expect to hit at least once gene twice with a probability of around .005 – making it a reasonably significant observation.

However, this is actually an overestimate of the significance, as differences in gene size, base composition, etc… make it more likely that a random mutation will land on some genes than others, thereby increasing the probability of seeing the same gene twice. The authors did extensive simulations that take this into account, and, restricting their analysis to the 80% of genes expressed in the brain, they conclude the observation of two nonsense/splicing variants in brain expressed genes is significant, at a p-value of 0.008.

However, it is worth noting (from the authors Figure S8) that under conservative but reasonable estimates of the de novo mutation rate and number of genes involved in ASD, the degree to which the data implicate SCN2A specifically is weaker, with a q-value (probability that the gene is not involved in ASD under various models) of around 0.03. Again, this may seem a bit counterintuitive, given that their data say that it’s significant that they saw the same gene twice, and they found only one such gene, how could that gene not be involved? But one actually has more power to validate the general model that de novo nonsense/splicing mutations are contributing to ASD than you do to implicate specific genes. This is why State’s assertion in the NYT that SCN2A was 99.9999% likely involved in ASD was pretty egregious – it is simply not consistent with their own data.

There are a few other things to note here.

First, the p-values and q-values they report is not specific to an individual gene – it is the average probability of observing a double hit in non-ASD genes and the average probability that a double-hit gene is involved in ASD. But SCN2A is relatively large (2000 amino acids), and thus the observation of two mutations in this gene is somewhat weaker evidence for its involvement in ASD than it would be for a smaller gene. I haven’t done a full simulations, but given that SCN2A is 4-5x larger than average, it should be on the order of 20x more likely to be doubly hit by chance than a typical gene, and thus the average q-value reported is an underestimate. It would be easy, using the simulations the authors already have on hand, to ask what the false-discovery rate when the doubly hit gene is 2000 amino acids or longer. I suspect it would not longer be significant.

The model also fails to consider the possibility that such fairly significant mutations in many genes might be lethal, and thus would never be observed. Hard to get a great estimate of what fraction of genes this might be, and the number is probably small given that they’ll almost all be heterozygous, but, again, given that the observations are only marginally significant, this possibility seems worth considering.

Finally, the more I read the paper, the more uncomfortable I grew with the way that the paper moved back and forth from non-synonymous to nonsense/splicing mutations, depending on where they got statistical significance. They start out by arguing that the there is a significant increase in the number of de novo synonymous mutations in ASD affected individuals. They get statistical significance here because there are a relatively large number of such mutations. They then look for cases where the same gene was hit twice, and find two. But this is not a significant observations – failing to distinguish between the possibility that a subset of ASD-involved genes were being hit from the null model of genes being hit randomly. However, for one of these pairs they noticed that there were two nonsense mutations. There wasn’t a significant enrichment of de novo nonsense mutations in cases (10) vs controls (5), so they added in the five splicing mutations from cases (there were none in controls) and got a marginally significant enrichment (p=.02). Then they looked at how likely it would be to find the same gene hit twice by nonsense/splicing mutations, and got a marginally significant result.

It’s possible to justify this path of analysis from first principles, as nonsense/splicing mutations are difference from missense mutations – and maybe this was part of the analysis design from the beginning. But the way the paper was set out, it felt that they were hunting for significant p-values – which is a big no-no. What if they had observed that highly conserved amino acids in some gene had been hit by the same missense mutation in two families? Would they have pursued this result and evaluated its significance? This is a crucial question, because if they pursued the nonsense observation simply because it was what they observed, then their statistics are wrong, as they need to be corrected for all the other possible double-hit leads they would have pursued. This is not a subtle effect either – such a correction would almost certainly render the results insignificant.

I don’t know the details of how this experiment was planned. Maybe they always intended to do this exact analysis in the first place, and thus it’s completely kosher. But the scientific literature is filled with post facto statistical analyses, in which people do an experiment, make an observation, and then evaluate the significance of this observation under the assumption that this was always what they were looking for in the first place.

It’s sort of like how, in baseball broadcasts, the announcers are always saying things like “This batter has gotten hits in his first at bat in 20 straight games played on Sunday afternoon”. They say this because it sounds so improbable – and in some sense it is, as this specific streak is, indeed, improbable. But if you consider all the possible ways you can slice and dice a player’s past performance, it is inevitable that there would be some kind of anomaly like this – rendering it statistically uninteresting.

I’m not saying that something this extreme happened in this autism paper. But the way the data were presented in the paper definitely made it seem like they were looking for a statistically significant observation on which to sell their paper (to Nature and to the public).

And it’s a shame – the data in the paper are cool. But does it really make sense to make such a big deal out of what is, at best, a single marginally significant observation? What if they hadn’t chosen one of those two families for their study? Would the result be uninteresting? Of course not.

In the end, what this paper should have said was, we generated a lot of cool data, we found some evidence that de novo mutations are enriched in kids with ASD relative to their siblings, but we need more data – a lot of it – to really figure out what’s going on here. Unfortunately, in the world we live in, this would have been dismissed as kind of boring, and likely not worthy of a Nature paper (although far less interesting genome papers are published there all the time).

So the authors made a big deal out of an interesting single observation, when they should have waited for more data. And then, probably for the same reasons, they oversold the result to the press – and ended up expressing an  indefensible 99.9999% confidence in SNC2A’s involvement in ASD to a reporter.

And I hope you understand now why it pissed me off.

Last week Nature published the results of three studies (1,2,3) looking at the sequences of protein-coding genes from hundreds of individuals with autism and their parents. The main results are that there is a higher rate of de novo mutations in affected individuals, that these primarily come from fathers, and that the affected genes are enriched for those involved in brain development and activity.

I think a bit too much is being made of these studies – they’re generally technically sound, but there remains no definitive link between any single mutation or groups of mutations and the disease. However, the authors of one of the papers have made a big deal about having found a mutation in the same gene in two unrelated individuals. This is described in a piece last week by Benedict Carey in the New York Times:

In one of the new studies, Dr. Matthew W. State, a professor of genetics and child psychiatry at Yale, led a team that looked for de novo mutations in 200 people who had been given an autism diagnosis, as well as in parents and siblings who showed no signs of the disorder. The team found that two unrelated children with autism in the study had de novo mutations in the same gene — and nothing similar in those without a diagnosis.

“That is like throwing a dart at a dart board with 21,000 spots and hitting the same one twice,” Dr. State said. “The chances that this gene is related to autism risk is something like 99.9999 percent.”

Wow. 99.9999 percent. That’s impressive. But I have no idea where it came from.

If the study had looked at exactly two families, and they had found a single de novo mutation in the affected individual in each family, and these had been in the same gene, then yes, it would have been like throwing a dart at a dart board with 21,000 spots (roughly the number of genes examined) and hitting the same one twice – or roughly 1 in 21,000. But this is not what they did.

The study actually examine 200 families with an affected and unaffected siblings, and identified 125 variants with the potential to alter protein function. So the question is not how likely it is to hit the same spot if you throw two darts, but rather how likely it is to hit the same spot if you throw 125 darts at a dart board with 21,000 spots. The answer is that you would expect to have two dots hit the same spot 30.9% of the time. That is roughly one in three times. In fact, the 30.9% number is a conservative estimate that assumes that the odds of hitting any given gene are the same – this is undoubtedly not the case, as some genes are bigger than others – so the real odds that that the authors would have found the same gene twice purely by chance are even greater. Either way, it’s a very far cry from 99.9999 percent odds against.

UPDATE: Now that I’ve had a chance to look at the paper in more detail, I realize the authors were making a more subtle point about the nature of the mutations involved – highlighting the fact that they found two non-sense or splice mutations in the same gene. The authors did some fairly sophisticated simulations of the chances of this occurring and found, if they restrict their analysis to genes expressed in the brain, that the chances of this occurring by chance are ~0.8%.

This is not the same as throwing darts at a dartboard with 21,000 genes as there are only 14,000 brain expressed genes. But I agree with the authors that this is not a trivially expected result. Though I still have no idea where the 99.9999% part of the quote came from. Four orders of magnitude is a big difference.

What’s annoying here is not so much that the NYT used this quote (though they really need someone around to check these kind of things), but rather that the quote came from the lead author of the paper – Matthew State – a clinical geneticist at Yale.

I can not believe State said this this way. I hope he was simply misquoted. But if he really said this, and assuming that then he understands the basic statistics involved (which, given his position, I find highly likely), then he must have oversimplified and somewhat misrepresented the significance of his findings in order to make it sound more impressive in the popular press.

——————-

For those interested in how I came up with the 30.9% number, even if it might not be relevant, the question we want to ask is how likely is it that if we picked a random gene 125 times from a set of 21,000 we would never pick the same gene twice. Think of it this way. The first gene we pick can not overlap another gene. When we pick the second gene, 20999 times out of 21000 (probability .99995238) it will not be the gene we picked first. When we pick the third gene, we assume the first two went into different boxes (otherwise we’d be done already) so the odds go down slightly, to 20998 times out of 21000 (.99990476) and they keep going down slightly each time until we get to gene 125 when the odds are 20876 out of 21000 (.99409524).

The counterintuitive part of this is that even though at each step the odds are low, in order to end up with all of the genes in different bins you have to be on the right side of that random probability at each of 124 different steps. And to calculate the odds of this, you have to multiple all of these numbers together: .99995238 * .99990476 * …. * .99409524 which equals .69088693. That means that there is only a 69.1 percent chance that all 125 randomly chosen genes will be different – or 1 30.9 percent chance that you’ll see at least one gene twice.

It’s the same logic as the classic probability question of how many people you have to have in a room for the odds to be greater than 50% that two of them share the same birthday – the answer being 22.

UPDATE: Several people here and on twitter complained that my analysis did not take into account the controls in the paper – and implied that the results would be very different if I did.

The controls have a completely negligible effect. The critique the commenters raised that the authors didn’t just observe two hits to the same gene in the autism cases, they observed no hits to that gene in the controls. The papers states that there were 87 relevant mutations in the controls. So, conditioned on the observation that some gene was hit twice in the cases, we want to know how likely it would be that you would not hit that gene in 87 controls. The answer is 99.6%.

So, whereas I stated originally that the probability of hitting the same gene twice by chance in 125 random samples from a pool of 21,000 genes was 30.9%, if we now ask what is the probability of hitting the same gene twice by chance in 125 random samples from a pool of 21,000 genes AND not hitting the same gene in a set of 87 controls, the answer is 30.8%.

It’s a provocative claim, and the paper was aggressively press-released. Vogelstein even held a press conference at a major cancer meeting to discuss it. And the media clearly loved the iconoclastic spin, giving the work a lot of exposure that largely parrots the authors’ anti-personal genome sequencing message.

From a strictly scientific standpoint, the paper does not deserve so much attention. It presents no new data, and its conclusions are not novel (Erick Check Hayden has a nice blog post about objections to the paper itself). If the work has any value, it is in framing the issues around the value of personal genome sequencing in a useful way for a non-technical audience.

The authors seem to recognize this. Not only have they sought popular press coverage of their work, but they led off their discussion in the paper with thoughts about the impact of their findings on public perceptions:

The general public does not appear to be aware that, despite their very similar height and appearance, monozygotic twins in general do not always develop or die from the same maladies . This basic observation, that monozygotic twins of a pair are not always afflicted by the same maladies, combined with extensive epidemiologic studies of twins and statistical modeling, allows us to estimate upper- and lower- bounds of the predictive value of whole-genome sequencing.

It is thus the height of irony that the actual paper is effectively not available to the public. Indeed, even with all the privileges of my affiliation with one of the largest research universities in the world (UC Berkeley), I could only read the abstract, and was instead offered “24 hours access to this Science Translational Medicine article for US $15.00″.

It is a shame that the authors who so clearly want their work to impact the public chose to publish it in a journal that even many of their colleagues – let alone the public – can not access. Prominent scientists like this should never let this happen – particularly when they view the public as part of their audience and they have a written a paper that likely would engage the public if they could read it.

But I reserve most of my disdain for the publisher - the non-profit American Association for the Advancement of Science, the world’s largest general scientific society. The AAAS talks a good game about the importance of engaging the public in scientific discourse, but they evidently don’t care about extending this engagement beyond the shallow platitudes of press releases.

I am sure the AAAS realize that the many in the public are actually interested in learning more about the details behind science stories they read about in the popular press. But rather than view this interest as a great opportunity for public engagement, the AAAS seems to view it as nothing more than an opportunity to make a quick buck.

————————————————————————————————–

The citation to the paper is:

Nicholas J. Roberts, Joshua T. Vogelstein, Giovanni Parmigiani, Kenneth W. Kinzler, Bert Vogelstein, and Victor E. Velculescu, “The Predictive Capacity of Personal Genome Sequencing”, Sci. Transl. Med. DOI: 10.1126/scitranslmed.3003380. 

And here is the PDF for those of you who don’t have friends who can access it and email you a copy.

————————————————————————————————–

[UPDATE: AAAS has changed the access rules for this paper, making it available for free to registered users.]

[UPDATE II: Since someone questioned my original statement that the article was not available to me through UC Berkeley, I am posting a screenshot I took this morning of the landing page for the full text of this paper followed by what it looks like now, both taken from within the Berkeley network, showing the original $15 pay for 24 hour access, and the new free access with registration]

]]> http://www.michaeleisen.org/blog/?feed=rss2&p=998 8 http://www.michaeleisen.org/blog/?p=996 http://www.michaeleisen.org/blog/?p=996#comments Wed, 07 Mar 2012 04:53:38 +0000 Michael Eisen http://www.michaeleisen.org/blog/?p=996 The American Association of Publishers and the anti-open access DC Principles group have sent letters to both houses of Congress outlining why they oppose the Federal Research Public Access Act, which would make the results of all federally funded research publicly available. They largely trot out the same tired “not all publishers are alike, so don’t impose a single model on all of us” baloney they’ve been using for years.

But one part of the letter really caught my eye:

[FRPAA] would also compel American taxpayers to subsidize the acquisition of important research information by foreign governments and corporations that compete in global markets with the public and private scientific enterprises conducted in the United States.

Huh? Think about what they’re saying: The US government should not make the results of taxpayer funded research available to all US citizens because it would also be made available to foreigners, which would give them a leg up over American companies in the competitive global marketplace. And how are the publishers going to protect us from this looming threat? By denying these nefarious foreign entities access to the information they are going to use to trounce us? No! The publishers want Congress to insist that these foreigners pay them a small fee to facilitate their fleecing of America.

COME ON! This one sentence exposes the publishers who wrote and signed the letter either as racist idiots who have no clue about how science works and what its goals are, or as craven liars willing to trot out xenophobic claptrap to promote their agenda.

We are not talking about classified information here – we’re talking about information that authors are willingly making freely available. And these foreigners the publishers are deriding are not enemies. They are our collaborators in science – whose ability to build on work generated in the US benefits us all. This is how science works, you morons!

Earlier in the letter, these signers of the letter claim that they are “devoted to ensuring wide dissemination of the results of all peer-reviewed research”. That they would then have the gall to put forward the argument that US interests are served by impeding to free flow of scientific information to scientists in other countries makes it clear that this is a complete and utter lie. This is one of the most repulsive things I have seen from the forces that oppose public access – anyone who signed this letter should be ashamed, and is deserving of our contempt.

This brazen act, which its backers hoped would pass unnoticed in the quiet of the holidays, was ultimately noticed (when the Association of American Publishers issued press release), and met with intense opposition (c.f. my op-ed in the NYT, the writings of Mike Taylor and of the twitter account FakeElsevier and many, many others) culminating in a growing boycott of Elsevier.

In previous years publishers brushed off such criticism with the typical impunity of a multi-billion dollar conglomerate faced with outcry from academics. But this time all the bad press clearly had an effect, as today Elsevier retracted its support for the RWA, as did the two members of Congress who introduced it!!

So let’s take a moment to celebrate this victory, and thank all the people who rose up to oppose this odious attempt to legislate the elevation of private profit over the public good. It is another testament to the power of collective action in social networks, blogs and the mainstream press, to go along with defeat of SOPA and PIPA earlier this year.

Elsevier and others who have opposed public access will obviously hope that their tactical retreat will damped the enthusiasm of their opponents. But let us not confuse victory in this skirmish with victory. Elsevier’s journals are no more accessible today than there were yesterday. And 85% of the published literature remains locked up behind publishers’ paywalls. We should not rest until that number drops to 0%. And, if anything, we should be emboldened by this success to realize that when scientists and the public scream loudly enough, we are heard and can change things for the better.

So, once again, congratulations. Pause to have a drink to celebrate. But then back to the trenches.

[UPDATE] Fixed a few typos, including an inadvertent celebration of public creaming.

Cambridge Journals has announced a brand new Article Rental scheme, which will see single academic research articles being made available over a 24-hour period at a significantly lower cost.

More brilliance from FakeElsevier cooked up to make fun of the absurdity of journals owning scientific papers. I could see their tweet immediately:

FakeElsevier: Can’t afford to pay £50 to “own” a copy of an article you want to read? No fears! We’ll rent it to you for 24 hours for £3.99!

But, sadly, this is NOT a joke. I hardly know where to begin. So I’ll start with the explanation offered by Simon Ross, Global Journals Director, Cambridge University Press:

Article Rental is a direct response to the increasingly high cost of full article ownership through the subscription, document delivery and pay-per view routes that non-subscribers have to use in order to access to an article.

Increasingly high cost? Do you know what the cost is going up? BECAUSE YOU GITS ARBITRARILY RAISED THE PRICE!!!! Don’t try to act like there forces outside of your control that you are rescuing people from, or that the pay-per-view price represents any kind of rational calculus.

CUP arbitrarily decided how much it would cost for people to “own” a copy of an article. They set this price ridiculously high. Nobody is buying. So instead of cutting the price to something sane (like free) they offer a ridiculous “no print, no save” 24 hour options and herald it as an awesome discount. It would be funny if it weren’t so repulsive.

And if this insanity doesn’t convince you that we need to abolish subscription-based journals and the oft-abused publisher control of the scientific literature it entails, then perhaps this piece of information will:

From our analysis of user traffic on Cambridge Journals Online, we see millions of non-subscribers turn away as they can only access the article title and abstract information. We can now provide an alternative low-barrier access route that will allow these readers to access the research that interests them.

Publishers have for years argued that there is no need for open access because most people who want access already have it through their institutions. But CUP is clearly saying this is not the case. Millions of non-subscribers turned away? MILLIONS!! I suspect they be just as unwilling to spend $6 for 24 hours as they were $25 or $50 or whatever they were charging before. There is no reason any of these millions should ever be denied the chance to read any article, or charged even a half-pence for the opportunity. We need open access. And we need it now.