The Tree of Life

Diversity (of speakers, participants) at meetings: do something about it

noreply@blogger.com (Jonathan Eisen) — Tue, 29 May 2012 08:49:00 +0000

Some unformed thoughts here but here goes.

Every so often I see a conference announcement and am annoyed by the XY/XX excess for the speakers. Some recent examples

Gairdner Foundation - Genome Canada "Genomics: the power and the promise"
IOM "Improving Safety Through One Health" (agenda here)
BGI "International Conference on Genomics in Europe"
BGI Genomics Meeting in US

And more.

Now - I complain about this here and there on Twitter and the like

40 Speakers at the BGI Genomics Meeting in US - 5 of them women - not good -shar.es/rEVh9
— Jonathan Eisen (@phylogenomics) April 20, 2012

Not impressed w/ the lack of diversity in the Genome Canada speakers featured here shar.es/qCvg1
— Jonathan Eisen (@phylogenomics) May 29, 2012

But I felt that this needed a blog post to not get lost in the Twitter stream. So here it is.

I note - I have posted about this issue previously: A conference where the speakers are all women? | The Tree of Life and for conference for which I am involved I have been trying very hard to work on the speaker diversity (not just XX vs XY, but age, career status, ethnicity, etc). And it certainly can be difficult to make sure that diversity is there. But the meetings I list above are pretty egregious. The Genome Canada one features seven major speakers - all white males. Yes, they are all big names. But in biology, where women are reasonably well represented, it suggests a bias to me if a meeting can somehow only manage to invite and/or attract all senior, white, XYs to be major speakers. Not sure what that bias is and it could be different in each case - could be who is invited - could be the field itself - could be timing/nature of the meeting - could be something to do with families (e.g., perhaps women are invited but are more likely to feel like limiting travel due to roles in child care).

Also I note - biases are not necessarily affecting any one gender or ethnic group. For example, I have generally stopped going to meetings/conferences that are on weekends and I have also stopped going to meetings/dinners after 6 PM because I do not want to skip out on time with my family.

So here is a plea. Next time you are involved in organizing a meeting - make some effort to have a strong representation of diversity of speakers and participants. For example, if you invite lots of women for example and all say no - try to figure out why and see if you can fix the issue. Offer travel fellowships for students. Offer child care or child activity options (even if you cannot pay for it - at least make it easy for people). Make sure to advertise/promote the meeting to groups/institutions with a high representation of underrepresented groups. Don't give up if your first efforts don't work. Sometimes it can be difficult to make sure diversity levels are high. But keep trying ... it will help make the conference better and also will help the field in general ...

Dubious Press Release from Cedars-Sinai linking Irritable Bowel Syndrome (IBS) and Bacteria in Gut

noreply@blogger.com (Jonathan Eisen) — Sun, 27 May 2012 08:37:00 +0000

Quick one here.

Not impressed with this press release from Cedar-Sinai: Dr. Pimentel links IBS and gut bacteria - Cedars-Sinai (see other variants of it here: Daily Disruption – Cedars-Sinai Study Links Irritable Bowel Syndrome (IBS) and Bacteria in Gut and here: Irritable bowel syndrome clearly linked to gut bacteria).

Among the things that bug me here:

They don't include a link to the paper or even provide a citation
They claim that culturing microbes is the "gold standard" for connecting bacteria to the cause of this disease. AND they imply this is the first method to use culturing to study the disease. Both notions are wrongheaded.
They confuse cause of IBS and symptoms. They say that b/c antibiotics help reduce symptoms, therefore, bacteria cause the disease. Really? So then fevers must cause things like malaria and flu because ibuprofen helps reduce symptoms right?
At some point it might be nice to mention that the MD behind the new study has also been pushing the idea that IBS is caused by bacterial overgrowth for many years both in a book and via a testing company though it is unclear what his association with the company is. I note - ads for the book claim " In addition, Dr. Pimentel presents a simple treatment protocol that will not only help you resolve your IBS symptoms, but will also prevent their recurrence." So - apparently he already had a cure BEFORE the new study was even done. I general I am skeptical of papers that show evidence for something coming from someone who apparently already "knew" the answer.

Of course, I am not saying IBS is NOT caused by bacterial overgrowth as they claim. But I can say this - PRs like this make me skeptical that anything new was done in this current publication.

Nice Collection from Diane Dawson: Open Science and Crowd Science: Selected Sites and Resources

noreply@blogger.com (Jonathan Eisen) — Sat, 26 May 2012 01:31:00 +0000

Quick post here - already posted to Twitter and wanted to make sure this one was seen by people who read this blog but don't follow me on Twitter.

There is a nice compilation/commentary/review from Diane Dawson titled Open Science and Crowd Science: Selected Sites and Resources. It is in the journal "Issues in Science and Technology Librarianship" (which I note - is a new one to me). It has a lot of useful resources and comments about various open science activities on the web. Definitely worth checking out.

Yum - Carbon monoxide, worms, bacteria - all together - what could be better

noreply@blogger.com (Jonathan Eisen) — Sat, 26 May 2012 01:26:00 +0000

Just a quick one here pointing people to a paper and some stories relating to work by Nicole Dubilier on the worm Olavius algarvensis and it's chemosynthetic symbionts.

The paper: "Metaproteomics of a gutless marine worm and its symbiotic microbial community reveal unusual pathways for carbon and energy use": Full Text (They paid for the PNAS Open Access option)
Research | Research news | A toxic menu
Elba: Scientists study gutless marine worm
Protein analysis investigates marine worm community (Press Release)
La asombrosa simbiosis de un gusano con bacterias le permite ...
Un ver marin qui se nourrit de composés toxiques
Seltsamer Meereswurm ernährt sich von Giften

Guest post: Story Behind the Paper by Joshua Weitz on Neutral Theory of Genome Evolution

noreply@blogger.com (Jonathan Eisen) — Fri, 25 May 2012 13:59:00 +0000

I am very pleased to have another in my "Story behind the paper" series of guest posts. This one is from my friend and colleague Josh Weitz from Georgia Tech regarding a recent paper of his in BMC Genomics. As I have said before - if you have published an open access paper on a topic related to this blog and want to do a similar type of guest post let me know ...

----------------------------------------
A guest blog by Joshua Weitz, School of Biology and Physics, Georgia Institute of Technology

Summary This is a short, well sort-of-short, story of the making of our paper: “A neutral theory of genome evolution and the frequency distribution of genes” recently published in BMC Genomics. I like the story-behind-the-paper concept because it helps to shed light on what really happens as papers move from ideas to completion. It's something we talk about in group meetings but it's nice to contribute an entry in this type of forum. I am also reminded in writing this blog entry just how long science can take, even when, at least in this case, it was relatively fast.

The pre-history The story behind this paper began when my former PhD student, Andrey Kislyuk (who is now a Software Engineer at DNAnexus) approached me in October 2009 with a paper by Herve Tettelin and colleagues. He had read the paper in a class organized by Nicholas Bergman (now at NBACC). The Tettelin paper is a classic, and deservedly so. It unified discussions of gene variation between genomes of highly similar isolates by estimating the total size of the pan and core genome within multiple sequenced isolates of the pathogen Streptococcus agalactiae.

However, there was one issue that we felt could be improved: how does one extrapolate the number of genes in a population (the pan genome) and the number of genes that are found in all individuals in the population (the core genome) based on sample data alone? Species definitions notwithstanding, Andrey felt that estimates depended on details of the alignment process utilized to define when two genes were grouped together. Hence, he wanted to evaluate the sensitivity of core and pan geonme predictions to changes in alignment rules. However, it became clear that something deeper was at stake. We teamed up with Bart Haegeman, who was on an extended visit in my group from his INRIA group in Montpellier, to evaluate whether it was even possible to quantitatively predict pan and core genome sizes. We concluded that pan and core genome size estimates were far more problematic than had been acknowledged. In fact, we concluded that they depended sensitively on estimating the number of rare genes and rare genomes, respectively. The basic idea can be encapsulated in this figure:

The top panels show gene frequency distributions for two synthetically generated species. Species A has a substantially smaller pan genome and a substantially larger core genome than does Species B. However, when one synthetically generates a sample set of dozens, even hundreds of genomes, then the rare genes and genomes that correspond to differences in pan and core genome size, do not end up changing the sample rarefaction curves (seen at the bottom, where the green and blue symbols overlap). Hence, extrapolation to the community size will not necessarily be able to accurately estimate the size of the pan and core genome, nor even which is larger!

As an alternative, we proposed a metric we termed “genomic fluidity” which captures the dissimilarity of genomes when comparing their gene composition.

The quantitative value of genomic fluidity of the population can be estimated robustly from the sample. Moreover, even if the quantitative value depends on gene alignment parameters, its relative order is robust. All of this work is described in our paper in BMC Genomics from 2011: Genomic fluidity: an integrative view of gene diversity within microbial populations.

However, as we were midway through our genomic fluidity paper, it occurred to us that there was one key element of this story that merited further investigation. We had termed our metric "genomic fluidity" because it provided information on the degree to which genomes were "fluid", i.e., comprised of different sets of genes. The notion of fluidity also implies a dynamic, i.e., a mechanism by which genes move. Hence, I came up with a very minimal proposal for a model that could explain differences in genomic fluidity. As it turns out, it can explain a lot more.

A null model: getting the basic concepts together
In Spring 2010, I began to explore a minimal, population-genetics style model which incorporated a key feature of genomic assays, that the gene composition of genomes differs substantially, even between taxonomically similar isolates. Hence, I thought it would be worthwhile to analyze a model in which the total number of individuals in the population was fixed at N, and each individual had exactly M genes. Bart and I started analyzing this together. My initial proposal was a very simple model that included three components: reproduction, mutation and gene transfer. In a reproduction step, a random individual would be selected, removed and then replaced with one of the remaining N-1 individuals. Hence, this is exactly analogous to a Moran step in a standard neutral model. At the time, what we termed mutation was actually representative of an uptake event, in which a random genome was selected, one of its genes was removed, and then replaced with a new gene, not found in any other of the genomes. Finally, we considered a gene transfer step in which two genomes would be selected at random, and one gene from a given genome would be copied over to the second genome, removing one of the previous genes. The model, with only birth-death (on left) and mutation (on right), which is what we eventually focused on for this first paper, can be depicted as follows:

We proceeded based on our physics and theoretical ecology backgrounds, by writing down master equations for genomic fluidity as a function of all three events. It is apparent that reproduction decreases genomic fluidity on average, because after a reproduction event, two genomes have exactly the same set of genes. Likewise, gene transfer (in the original formulation) also decreases genomic fluidity on average, but the decrease is smaller by a factor of 1/M, because only one gene is transferred. Finally, mutation increases genomic fluidity on average, because a mutation event occurring at a gene which had before occurred in more than one genome, introduces a new singleton gene in the population, hence increasing dissimilarity. The model was simple, based on physical principles, was analytically tractable, at least for average quantities like genomic fluidity, and moreover it had the right tension. It considered a mechanism for fluidity to increase and two mechanisms for fluidity to decrease. Hence, we thought this might provide a basis for thinking about how relative rates of birth-death, transfer and uptake might be identified from fluidity. As it turns out, many combinations of such parameters lead to the same value of fluidity. This is common in models, and is often referred to as an identifiability problem. However, the model could predict other things, which made it much more interesting.

The making of the paper
The key moment when the basic model, described above, began to take shape as a paper occurred when we began to think about all the data that we were not including in our initial genomic fluidity analysis. Most prominently, we were not considering the frequency at which genes occurred amongst different genomes. In fact, gene frequency distributions had already attracted attention. A gene frequency distribution summarizes the number of genes that appear in exactly k genomes. The frequency with which a gene appears is generally thought to imply something about its function, e.g., "Comprising the pan-genome are the core complement of genes common to all members of a species and a dispensable or accessory genome that is present in at leastbone but not all members of a species." (Laing et al., BMC Bioinformatics 2011). The emphasis is mine. But does one need to invoke selection, either implicitly or explicitly, to explain differences in gene frequency?

As it turns out, gene frequency distributions end up having a U-shape, such that many genes appear in 1 or a few genomes, many in all genomes (or nearly all), and relatively few occur at intermediate levels. We had extracted such gene frequency distributions from our limited dataset of ~100 genomes over 6 species. Here is what they look like:

And, when we began to think more about our model, we realized that the tension that led to different values of genomic fluidity also generated the right sort of tension corresponding to U-shaped gene frequency distributions. On the one-hand, mutations (e.g., uptake of new genes from the environment) would contribute to shifting the distribution to the left-hand-side of the U-shape. On the other hand, birth-death would contribute to shifting the distribution to the right-hand side of the U-shape. Gene transfer between genomes would also shift the distribution to the right. Hence, it seemed that for a given set of rates, it might be possible to generate reasonable fits to empirical data that would generate a U-shape. In doing so, that would mean that the U-shape was not nearly as informative as had been thought. In fact, the U-shape could be anticipated from a neutral model in which one need not invoke selection. This is an important point as it came back to haunt us in our first round of review.

So, let me be clear: I do think that genes matter to the fitness of an organism and that if you delete/replace certain genes you will find this can have mild to severe to lethal costs (and occasional benefits). However, our point in developing this model was to try and create a baseline null model, in the spirit of neutral theories of population genetics, that would be able to reproduce as much of the data with as few parameters as possible. Doing so would then help identify what features of gene compositional variation could be used as a means to identify the signatures of adaptation and selection. Perhaps this point does not even need to be stated, but obviously not everyone sees it the same way. In fact, Eugene Koonin has made a similar argument in his nice paper, Are there laws of adaptive evolution: "the null hypothesis is that any observed pattern is first assumed to be the result of non-selective, stochastic processes, and only once this assumption is falsified, should one start to explore adaptive scenarios''. I really like this quote, even if I don't always follow this rule (perhaps I should). It's just so tempting to explore adaptive scenarios first, but it doesn't make it right.

At that point, we began extending the model in a few directions. The major innovation was to formally map our model onto the infinitely many alleles model of population genetics, so that we could formally solve our model using the methods of coalescent theory for both cases of finite population sizes and for exponentially growing population sizes. Bart led the charge on the analytics and here's an example of the fits from the exponentially growing model (the x-axis is the number of genomes):

At that point, we had a model, solutions, fits to data, and a message. We solicited a number of pre-reviews from colleagues who helped us improve the presentation (thank you for your help!). So, we tried to publish it.

Trying to publish the paper
We tried to publish this paper in two outlets before finding its home in BMC Genomics. First, we submitted the article to PNAS using their new PNAS Plus format. We submitted the paper in June 2011 and were rejected with an invitation to resubmit in July 2011. One reviewer liked the paper, apparently a lot: "I very much like the assumption of neutrality, and I think this provocative idea deserves publication." The same reviewer gave a number of useful and critical suggestions for improving the manuscript. Another reviewer had a very strong negative reaction to the paper. Here was the central concern: "I feel that the authors' conclusion that the processes shaping gene content in bacteria and primarily neutral are significantly false, and potentially confusing to readers who do not appreciate the lack of a good fit between predictions and data, and who do not realise that the U-shaped distributions observed would be expected under models where it is selection that determines gene number." There was no disagreement over the method or the analysis. The disagreement was one of what our message was.

I still am not sure how this confusion arose, because throughout our first submission and our final published version, we were clear that the point of the manuscript was to show that the U-shape of gene frequency distributions provide less information than might have been thought/expected about selection. They are relatively easy to fit with a suite of null models. Again, Koonin's quote is very apt here, but at some basic level, we had an impasse over a philosophy of the type of science we were doing. Moreover, although it is clear that non-neutral processes are important, I would argue that it is also incorrect to presume that all genes are non-neutral. There's lots of evidence that many transferred genes have little to no effect on fitness. We revised the paper, including and solving alternative models with fixed and flexible core genomes, again showing that U-shapes are rather generic in this class of models. We argued our point, but the editor sided with the negative review, rejecting our paper in November after resubmission in September, with the same split amongst the reviewers.

Hence, we resubmitted the paper to Genome Biology, which rejected it at the editorial level after a few week delay without much of an explanation, and at that point, we decided to return to BMC Genomics, which we felt had been a good home for our first paper in this area and would likely make a good home for the follow-up. A colleague once said that there should be an r-index, where r is the number of rejections a paper received before ultimate acceptance. He argued that r-indices of 0 were likely not good (something about if you don't fall, then you're not trying) and an r-index of 10 was probably not good either. I wonder what's right or wrong. But I'll take an r of 2 in this case, especially because I felt that the PNAS review process really helped to make the paper better even if it was ultimately rejected. And, by submitting to Genome Biology, we were able to move quickly to another journal in the same BMC consortia.

Upcoming plans
Bart Haegeman and I continue to work on this problem, from both the theory and bioinformatics side. I find this problem incredibly fulfilling. It turns out that there are many features of the model that we still have not fully investigated. In addition, calculating gene frequency distributions involves a number of algorithmic challenges to scale-up to large datasets. We are building a platform to help, to some extent, but are looking for collaborators who have specific algorithmic interests in these types of problems. We are also in discussions with biologists who want to utilize these types of analysis to solve particular problems, e.g., how can the analysis of gene frequency distributions be made more informative with respect to understanding the role of genes in evolution and the importance of genes to fitness. I realize there are more of such models out there tackling other problems in quantitative population genomics (we cite many of them in our BMC Genomics paper), including some in the same area of understanding the core/pan genome and gene frequency distributions. I look forward to learning from and contributing to these studies.

Nathan Wolfe talk at #UCDavis Wrap Up #Storify #Viruses

noreply@blogger.com (Jonathan Eisen) — Fri, 25 May 2012 06:35:00 +0000

Nathan Wolfe talked at UC Davis yesterday. I met with him for 30 minutes just before his talk. Many times I feel that 30 minutes is more than enough when meeting with outside seminar speakers. I definitely would have enjoyed more time with Wolfe - he does some pretty fascinating stuff.

Anyway - I escorted him to his talk and then I took notes for it on Twitter as did Pam Ronald (who was sitting next to me). I then made a "Storification" of the talk (using the Storify.Com system).

This is below:

Wow - ALVIN submarine has potential to be vector for species movement cc: @deepseanews

noreply@blogger.com (Jonathan Eisen) — Thu, 24 May 2012 11:09:00 +0000

Well, it is (relatively) common knowledge that surface ships can serve as unintentional vectors for the movement of organisms via things like ballast water (see for example this recent post on Deep Sea News which discusses this in part). And the ecological favor wreaked by such ship-based-transport can be immense.

A new paper, and news story, call attention to an analogous process that might occur with deep-sea submarines (see news story here: U.S. News - Deep-sea aliens hitched ride by submarine to pristine area). The basic summary is - researchers using the deep sea sub ALVIN have discovered that, contrary to expectations, some organisms from the deep were able to survive the sub surfacing, being brought on board the mother ship, and then being sent back down to another site. Some limpets apparently hung out in some tubing for a day and were then "sampled" by the sub at another site. Apparently, nobody had thought this might be an issue because they had assumed that the surfacing and bringing on deck and cleaning of ALVIN would kill any organisms from one site before traversing to the next place. Apparently not.

I note one comment - it seems reasonable to think that microbes might be hitching a ride on ALVIN and other submersibles too ... which brings me back to the recent post on Deep Sea News I linked to above. It is by Holly Bik, a post doc in my lab, and in it she discussed the possibility that microbes might be getting moved around by surface ships. Well, it seems that submersibles should be looked at too ..

Smells like a SCAM: Invitation to Participate in the East African Universities' Lecture Series and a Safari

noreply@blogger.com (Jonathan Eisen) — Thu, 24 May 2012 06:40:00 +0000

Hmm ... this smells off. Must be as SCAM somewhere in here.

---------- Forwarded message ----------
From: Tours of Purpose (TOP) <info@toursofpurpose.com>
Date: Wed, May 23, 2012 at 9:29 PM
Subject: Invitation to Participate in the East African Universities'
Lecture Series and a Safari

Dear University of California Faculty and Staff:

Tours of Purpose, TOP, a professor exchange agency dedicated to the
development and improvement of economic, academic and general welfare
in East Africa (i.e., Uganda, Kenya, Tanzania, Rwanda and Burundi) is
hereby extending a humble invitation to you to participate in our
ongoing program of lecture series taking place in our local
universities, colleges, high schools, primary schools and other
academic institutions. Additionally, TOP would like to avail to you a
one in a lifetime opportunity to take a safari where you will see and
photograph lions, elephants, giraffes, leopards, zebras, hippos,
rhinos, among an array of wildlife, in addition to a rare opportunity
to visit the mountain gorillas and man's closest relative, the chimp,
at a TOP' scholars' give away price. Winston Churchill took this trip
and immortally dabbed Uganda "The Pearl of Africa", and Queen
Elizabeth was on such a safari when she learned that she had become
queen of England. The average visit lasts for about two weeks--with a
couple of days or so dedicated to visiting the said incredible African
wildlife reserves--although you may wish for your particular visit to
be shorter or longer. TOP would like to partner with a specific
professor, or any academician, in pursuing a possibility of coming to
East Africa to deliver lectures in any given dispositive academic
discipline. TOP will cooperate with you in arranging and customizing
your travel details to Africa, including picking you up at the airport
in TOP state of the art SUVs, booking fair accommodation, arranging
your meals, setting and managing your speaking schedule, taking you on
a safari trip and other tours, and ultimately delivering you to the
airport for your flight home. TOP invariably offers the option of one
being paired with another educator from North America or Europe during
this trip, although traveling alone in East Africa is not complicated
nor precarious at all.

Thus, if TOP secures your willingness to participate, TOP will, first,
discuss with you the financial side of it, including revealing what
assistance may be available for you in this regard so that you can
achieve your $1,200 or so round trip air ticket. Second, where a
Holiday Inn-style room costs about $180 a night in East Africa, TOP
offers you even better accommodation in our partnering hotel, Giraffe
Park Hotel, at $350 a week, breakfast and dinner inclusive. Lunch can
be packed or arranged very reasonably. As a TOP scholar, you also
qualify for $200 towards your travel expenses.

Consider, too, should you have plans of traveling to or through
Europe, why not shoot two birds with one stone by detouring through
East Africa for the instant, noble purpose and halve the costs, not to
mention the time to be saved or to be well used. Take note, too, that
in addition to some of your students who may either just want to
accompany you or do an internship here, you can invite your family and
friends as well.

As such, your willingness to participate dwarfs all financial
concerns, for TOP stands with you to make this trip not only
economical but, most importantly, simple to handle all around. In
fact, as an American educator, you are due to discover that your worth
to the vast world's academic needs is patently inestimable and that
sharing your expertise inures a hidden fulfillment.

In sum, this email cannot answer all the questions you might have
regarding this trip, therefore, you are encourage to contact me so
that we can further this conversation, including chatting on the
phone, if you desire. Needless to say, I, or a TOP representative,
will be available to talk with you about either an immediate trip or
to muse about a distant future possibility for this lectureship, in
addition to whether TOP, in conjunction with our local institutions,
should promulgate a concrete, personalized proposal for your
consideration.

Lastly, feel very welcome to visit our website (http://www.toursofpurpose.com
) to learn more about us and to view photos and read up on
testimonials of past participants. Also, on the website you will be
able to either join us on Facebook or to follow us on twitter.

Therefore, we hope to hear from you soon.

Sincerely,

~Josephine Nakandi
Program Director

--
~~~~~~~~~~~~~~~~~~~~~~~~
Tours of Purpose, TOP
49 Nakawa Road, Suite 400
Kampala, Uganda, East Africa
Tel: +256 778 899 429
info@toursofpurpose.com
http://www.toursofpurpose.com
~~~~~~~~~~~~~~~~~~~~~~~~

Kimberly-Clark's deceptive self serving PR regarding germs in the workplace #BadReportingToo

noreply@blogger.com (Jonathan Eisen) — Thu, 24 May 2012 03:22:00 +0000

First I saw of this story was here: Study: Bacteria fills office break rooms - Local News - Houston, TX - msnbc.com

Something sounded off with this. I think it was the fact that it involved "Cleaning products company Kimberly-Clark" that raised some alarm bells. The involvement of Charles Gerba also left me a bit queasy as I have seen his name associated with a few recent "studies" which are basically germaphobia funded by cleaning product companies.

After looking around a bit I got discouraged at the whole thing and put it out of my head for a few hours. And then David Coil, a post doc in my lab, sent me a link to the press release behind this story. And boy is it a doozy.

The PR basically makes the following dubious statements or implications
* All bacteria are bad. The whole PR references a study that they imply is about detecting bacteria in various locations. And when they detect high levels they conclude this is bad. For example in the title "Where the Germs Are: New Study Finds Office Kitchens and Break Rooms are Crawling with Bacteria". Or in the text: "If you thought the restroom was the epicenter of workplace germs you don't want to know about office break rooms and kitchens" "office germ "hot-spots,"" "Office workers are potentially being exposed to illness-causing bacteria right in their own lunchrooms" and much more. Uggh. Not all bacteria are bad. Gerba and Kimberly-Clark must know this yet they purposefully mislead.

* Presence of ATP means presence of bacteria (and see above - this must imply presence of bad bacteria). Wow. Not sure what to say here. But they use a test for ATP which they say "ATP is present in all animal, vegetable, bacteria, yeast and mold cells. Detection of ATP indicates the presence of contamination by any of these sources. Everyday objects with an ATP reading of 300 or higher are considered to have a high risk for illness transmission." No citation given. And sounds highly dubious to go from ATP - > risk for illness. Sounds completely dubious actually.

* That it is OK to make claims in Press Releases without presenting evidence behind the claims. The PR tries to make this all seem very scientific. Well, where is the paper behind this? They claim "The findings are from a study carried out by Kimberly-Clark Professional* and is believed to be one of the most detailed and comprehensive studies ever conducted on identifying workplace hotspots where germs can lurk." Where is the actual data? Where are the methods described? Yuck.

Alas - despite the fact that the Press Release is at best a self serving piece of dubious scientific quality - the press has run with the story sucking up everything Gerba and Kimberly Clark are saying. Ugg. Here are some examples, many of which really do a poor job on the science and the conflicts of interest inherent in an unpublished study from a cleaning products company

I am getting sick and tired of crap like this. Kimberly-Clark may make some useful products. I don't really know. But deceptive press releases like this suggest that their dedication to science is, well, low. They need to clean up their act.

What to do - what to do - cool microbial art w/ a #badomics word --- must resist purchasing -- must resist ...

noreply@blogger.com (Jonathan Eisen) — Tue, 22 May 2012 17:17:00 +0000

OK - thanks to Dan Smith for pointing me to: Phonome original watercolor painting bacteria by artologica

This was inspired in part by phone sampling I helped Dan and Jack Gilbert do at the AAAS meeting. And Michelle Banks (i.e., @artologica) has not only made microbial art out of it but has coined a new OME word. I think she is aiming directly at me here ... must resist. Must resist.

Story behind the paper guest post on "Resolving the ortholog conjecture"

noreply@blogger.com (Jonathan Eisen) — Fri, 18 May 2012 17:37:00 +0000

This is another in my ongoing "Story behind the paper series". This one is from Christophe Dessimoz on a new paper he is an author on in PLoS Computational Biology that is near and dear to my heart.

See below for more. I am trying to post this from Yosemite National Park without full computer access so I hope the images come through. If not I will fix in a few days.

.................

I'd like to thank Jonathan for the opportunity to tell the story behind our paper, which was just published in PLoS Computational Biology. In this work, we corroborated the "ortholog conjecture"—the widespread but little tested notion that orthologs tend to be functionally more conserved than paralogs.

I'd also like to explore more general issues, including the pitfalls of statistical analyses on highly heterogeneous data such as the Gene Ontology, and the pivotal role of peer-reviewers.

Like many others in computational biology, this project started as a quick analysis that was meant to take "just a few hours" but ended up keeping us busy for several years...

The ortholog conjecture and alternative hypotheses

The ortholog conjecture states that on average and for similar levels of sequence divergence, genes that started diverging through speciation ("orthologs") are more similar in function than genes that started diverging through duplication ("paralogs"). This is based on the idea that gene duplication is a driving force behind function innovation. Intuitively, this makes sense because the extra copy arising through duplication should provide the freedom to evolve new function. This is the conventional dogma.

Alternatively, for similar levels of sequence divergence, there might not be any particular difference between orthologs and paralogs. It is the simplest explanation (per Ockham's razor), and it also makes sense if the function of a gene is mainly determined by its protein sequence (let's just consider one product per gene). Following this hypothesis, we might expect considerable correlation between sequence and function similarity.

But these are by no means the only two possible hypotheses. Notably, Nehrt and colleagues saw higher function conservation among within-species homologs than between-species homologs, which prompted them to conclude: "the most important aspect of functional similarity is not sequence similarity, but rather contextual similarity". If the environment ("the context") is indeed the primary evolutionary driving force, it is not unreasonable to speculate that within-species paralogs could evolve in a correlated manner, and thus be functionally more similar than their between-species counterparts.

Why bother testing these hypotheses?

Testing these hypotheses is important not only for better understanding gene function evolution in general, but it also has practical implications. The vast majority of gene function annotations (98% of Gene Ontology annotations) are propagated computationally from experimental data on a handful of model organisms, often using models based on these hypotheses.

How our work started

Our project was born during a break at the 10^th anniversary meeting of the Swiss Institute of Bioinformatics in September 2008. I was telling Marc Robinson-Rechavi (University of Lausanne) about my work with Adrian Altenhoff on orthology benchmarking (as it happens, another paper edited by Jonathan!), which had used function similarity as a surrogate measure for orthology. We had implicitly assumed that the ortholog conjecture was true—a fact that Marc zeroed in on. He was quite sceptical of the ortholog conjecture, and around this time, together with his graduate student Romain Studer, he published an opinion in Trends in Genetics unambiguously entitled “How confident can we be that orthologs are similar, but paralogs differ?” (self-archived preprint). So, having all that data on hand, we flipped our analysis on its head and set out to compare the average Gene Ontology (GO) annotation similarity of orthologs vs. paralogs. Little did we think that this analysis would keep us busy for over 3 years!

First attempt

It only took a few weeks to obtain our first results. But we were very puzzled. As Nehrt et al. would later publish, we observed that within-species paralogs tended to be functionally more conserved than orthologs. At first we were very sceptical. After all, Marc had been leaning toward the uniform ortholog/paralog hypothesis, and I had expected the ortholog conjecture to hold. We started controlling for all sorts of potential sources of biases and structure in the data (e.g. source of ortholog/paralog predictions, function and sequence similarity measures, variation among species clades). A year into the project, our supplementary materials had grown to a 67-page PDF chock-full of plots! The initial observation held under all conditions. By then, we were starting to feel that our results were not artefactual and that it was time to communicate our results. (We were also running out of ideas for additional controls and were hoping that peer-reviewers might help!)

Rejections

We tried to publish the paper in a top-tier journal, but our manuscript was rejected prior to peer-review. I found it frustrating that although the work was deemed important, they rejected it prior to review over an alleged technical deficiency. In my view, technical assessments should be deferred to the peer-review process, when referees have the time to scrutinise the details of a manuscript.

Genome Research sent our manuscript out for peer-review, and we received one critical, but insightful report. The referee contended that our results were due to species-specific factors, which arise because “paralogs in the same species tend to be 'handled' together, by experimenters and annotators”. The argument built on one example which we had discussed in the paper: S. cerevisiae Cdc10/Cdc12 and S. pombe Spn2/Spn4 are paralogs inside each species, while Cdc10/Spn2 and Cdc12/Spn4 are the respective pairs of orthologs. The Gene Ontology annotations for the orthologs were very different, while the annotations of theparalogs were very similar. The reviewer looked at the source articles indetail, and noticed that "the functional divergence between these genes is more apparent than real". Both pairs of paralogs were components of theseptin ring. The differences in annotation appeared to be due to differences in the experiments done and in the way they were transcribed. The reviewer stated:

"A single paper will often examine the phenotype of several paralogs within onespecies, resulting in one paper, which is presumably processed by one GO annotator at one time. In contrast, phenotypes of orthologs in different species almost always come from different papers, via different annotation teams."

Authorship effect: an easily overlooked bias

At first, it was tempting to just dismiss the criticism. After all, as Roger Brinner put it, "the plural of anecdote is not data." More importantly, we had tried to address several potential species-specific biases, such as uneven annotation frequencies among species (e.g. due to developmental genes being predominantly studied in C. elegans). And we had been cautious in our conclusions, suggesting that our results might be due to an as yet unknown confounder in the Gene Ontology dataset (remember that we had run out of ideas?). So the referee was not telling us anything we did not know.

Or was (s)he? Stimulated by the metaphor of same-species paralogs being "handled" together, we decided to investigate whether common authorship might correlate in any way with function annotation similarity. Here's what we observed:

The similarity of function annotations from a common paper is much higher than otherwise! Even if we restrict ourselves to annotations from different papers, but with at least one author in common, the similarity of functional annotations is still considerably higher than with papers without a common author.

Simpson's Paradox

In itself, the authorship effect is not necessarily a problem: if annotations between orthologs and paralogs were similarly distributed among the different types, differences due to authorship effects would average out. The problem here is that paralogs are one order of magnitude more likely to be annotated by the same lab than orthologs. This gives rise to "Simpson's paradox": paralogs can appear to be functionally more similar than orthologs just because paralogs are much more likely to be studied by the same people.

A classical example of Simpson's paradox is the "Berkeley gender bias case" (Wikipedia article): the university was sued for bias against women applicants based on the aggregate 1973 admission figures (44% men admitted vs. 35% women). As it turned out, the admission rate for each department was in fact similar for both sexes (and even in favour of women in a few departments). The lower overall acceptance rate for women was not due to gender bias, but to the tendency of women to apply to more competitive departments.

Paper by Nehrt et al.

Finding the authorship effect meant that we had to reanalyse all our data, and completely rewrite our manuscript. A few months into this process, in June 2011, Matt Hahn and colleagues published their paper (Nehrt et al., Testing the Ortholog Conjecture with Comparative Functional Genomic Data from Mammals, PLoS Comput Biol 2011). Matt has written a very interesting story behind the paper on this blog, which is well-worth reading (including comments).

While we weren't very surprised by the essence of their observations—they were very consistent with our initial (rejected) manuscript—we were nevertheless struck by the similarity in the presentation of the results:

On the left, plot 2A from Nehrt et al., PLoS Comput Biol 2011; On the right, plot from our initial, rejected manuscript. Note that their blue (within-spec outparalogs) and green (inparalogs) lines are combined in our plot (same-species paralogs, yellow line)

The publication of Nehrt et al.'s gave us mixed feelings. Obviously, their work was taking away some of the novelty in our study. But at the same time, they were drawing considerable attention to the problem (not least by coining a catchy name to describe the question!). And of course, we already knew at this point that their observations were confounded by factors such as the authorship effect, so it was not the end of the story.

Is it possible to draw reliable conclusions from observational data such as GO annotations?

Before I move to our findings, it's worth pondering a bit more on the issue of biases in the data. Statisticians and epidemiologists make a strong distinction between experimental data (=data from a controlled experiment, designed such that the case and control groups are as identical as possible in all respects other than a factor of interest) and observational data (=data lying around). (On a side note, Ewan Birney recently wrote a great post on study design in genetic and phenotypic studies, with several ideas relevant to this issue.) Data pulled from the GO database clearly falls into the second category: observational data. We are at the mercy of potentially countless hidden effect biasing our conclusions in all sorts of ways.

Can we rely on this data at all? For some, the answer appears to be a categorical "no". A more pragmatic stance was expressed by the GO consortium in a recent reply to Nehrt et al.'s paper, which identified potential confounding effects ignored in the study of Nehrt et al., such as species-specific annotation biases (they suggested, tongue-in-cheek, that the study instead supports the "biased annotation conjecture"), and stressed that "users of GO should ensure that they test for, and adjust for, potential biases prior to interpretation".

In the end, I think that this debate, consistent with our experience, highlights the risks of working with observational data. But at the same time, observational data is often all we have (or can afford), so the best course of action seems indeed to control for known confounders, try to identify unknown ones, and cautiously process forward.

Resolving the conjecture

Controlling for the authorship effect and other biases—some previously known, others newly identified—we found that for similar levels of divergence, orthologs tend to be functionally more conserved than paralogs. This is true for different source of orthology/paralogy predictions, different types of function and sequence similarity measures, and different data sampling strategies. But in absolute terms, the difference is often not very strong, and varies considerably among species and types of functions. Our study confirms the ortholog conjecture, but at the same time it shows that the conjecture is not very useful in practice as it does not have much predictive power.

They were two crucial contributors to this study: the peer-reviewers, and open science. We are obviously indebted to the reviewer who rejected our paper on the basis of a potential authorship bias. The reviewers of the resubmission provided detailed and highly competent feedback As for open science, where would computational biology be without it? We often take it for granted, but without publicly available genome data and functional annotations, a study like this would never have happened. Chemistry suffers from having only very few publicly available databases (e.g. ChEMBL). People hard at work behind model organism databases have our deepest appreciation.

Upcoming discussions

As far as I can tell, Nehrt et al.'s study caused a considerable stir in our community, but many critics could not quite put their finger precisely on what was wrong (see Matt Hahn's post, especially section "The fallout, and some responses"). Our work explains and reconciles their controversial observations.

This is by no means the end of the discussion. There will be a symposium dedicated to the ortholog conjecture at SMBE in Dublin next month (let me know if you want to meet up), and it will almost certainly be a topic of the next Quest for Orthologs meeting (tentatively scheduled for the summer 2013). Meanwhile, I hope this work will spur discussions on this blog (or, in French, on Marc Robinson-Rechavi's blog!) and/or on Twitter (you can follow me at @cdessimoz, and Marc at @marc_rr).

Thanks to Marc Robinson-Rechavi and Mary Todd Bergman for their feedback on drafts of this post.

Interesting report from White House: National Bioeconomy Blueprint

noreply@blogger.com (Jonathan Eisen) — Thu, 17 May 2012 14:32:00 +0000

Been reading the "National Bioeconomy Blueprint" from the WhiteHouse. It is is definitely worth checking out (for some background information see his blog post from the White House: National Bioeconomy Blueprint Released | The White House and this NY Times article White House Promotes a Bioeconomy - NYTimes.com from last month). Also check out the main page describing this document: National Bioeconomy Blueprint | The White House.

The blueprint outlines five main objectives:

Support R&D investments that will provide the foundation for the future U.S. bioeconomy.
Facilitate the transition of bioinventions from research lab to market, including an increased focus on translational and regulatory sciences.
Develop and reform regulations to reduce barriers, increase the speed and predictability of regulatory processes, and reduce costs while protecting human and environmental health.
Update training programs and align academic institution incentives with student training for national workforce needs.
Identify and support opportunities for the development of public-private partnerships and precompetitive collaborations—where competitors pool resources, knowledge, and expertise to learn from successes and failures.

And then goes through some background and recommendations to help achieve these objectives.

Other discussion of this includes:

Something fishy with this story: bacteria in fish pedicures

noreply@blogger.com (Jonathan Eisen) — Thu, 17 May 2012 07:34:00 +0000

Well, the title drew me in, without a doubt: Fish Pedicures: Bacteria in Your Foot Soak.

To start with _ i guess I have been out of touch as I have never heard of fish pedicures before. Sounds lovely I must say.

Though if you are considering doing this you might be dissuaded by some of the revelations in the article including that "fish are living creatures that deposit their waste products in the very water in which people are soaking" and "the impossibility of disinfecting or sanitizing live fish."

Amazingly, fish pedicures are in fact apparently quite popular. So popular that there are multiple investigations relating to this practice including that "British authorities investigated a reported bacterial outbreak among 6,000 Garra rufa fish " and "Last spring, British fish inspectors went to London's Heathrow Airport and intercepted Indonesian shipments of the silver, inch-long freshwater carp destined for British "fish spas."

And now - the reason for this article - there is a new report in the journal Emerging Infectious Diseases on "Zoonotic Disease Pathogens in Fish Used for Pedicure." The article is actually somewhat fascinating and thanks to the CDC it is freely available.

Fun reading for the day ...

Sign of the apocalypse? Science conference SPAM hybridizes w/ Nigerian advanced fee SPAM.

noreply@blogger.com (Jonathan Eisen) — Wed, 16 May 2012 06:02:00 +0000

Normally I do not share SPAM emails. But I have posted occasionally about Journal SPAM and Conference SPAM. So what do I do here. I just received an email that appears to be a hybrid between Conference SPAM and Nigerian advanced fee SPAM. OMG. The merging of two SPAM systems. Too bad the Conference is not about viagra - though since it is about Metagenomics perhaps it somehow got flagged due to studies of the penis or vagina microbiome? In this case I just had to post ...

Dear Honored Sir or Madam,

I am Prof. Mohammed Kaoje Abubakar minister of Science for the Republic of Nigeria under former President Alhaji Umaru Musa Yar’Adua. In this role I became in control of large sums of money dedicated to scientific research and the exchange of ideas with researchers from across the globe. However, since the time of the unfortunate death of President Yar'Adua, I have been under intense scrutiny of the new director of the ministry and have been unable to complete my mission. Fortunately, I remain in charge of most of the 200 million dollars US, but the current government will only release the funds in conjunction with scientific activities involving prominent foreign national scientists like yourself.

Therefore, on behalf of the 3rd Nigerian Congress of Metagenomics I am pleased to welcome you to propose a speech on your recent discovery about the genomic basis for the origin and evolution of new functions at the congress by submitting your speech title and CV to us. Meanwhile, we hope you can share your stimulating data, valuable scientific information and influential experiences with other industrial leaders, professionals and research pioneers. You are encouraged to network and explore partnering opportunities.

As a branded Conference of Nigeria Congresses LLC, "Your Think Tank", NCM continues to expand with magnificent scientific and social programs to maximize your network in a free communication meeting environment.

Activities of NCM 2012

l Keynote Forum – Presentations from Nobel Prize Laureate and Senior Leaders of Renowned Company

l Parallel Forum – 200+ Sessions and Symposiums provide 1000+ speech opportunities for experts from all of the world

l Welcome Banquet – All the participants enjoy the formal buffet dinner with wonderful performance show

l Project Matching Activity – Develop effective platform by free booths supply

l Keymakers Summit – Special Forum for Enterprisers to discuss hot issues face to face

l Exhibition and Poster Zone

The 3rd Nigerian Congress of Metagenomics is initiated for filling the gap between Eastern and West World for metagenomic professionals of free information exchange. In the past decade, NCM has attracted more than 5,000 enthusiastic speakers to communicate on the R & D advances in different therapeutic fields, which have generated great impact on the Chinese Bio/pharmaceutical development, enhanced Research and Development outsourcing, helped regional liaison of big pharma seeking partnership and searching talents, created a lot of opportunities for face-to-face network for multilateral collaboration by sharing both scientific and technological breakthroughs and speed up the process of many challenging drug discovery projects.

For more information PS: http:www.ncm.ng

Warri is a major oil city in Delta State, Nigeria, with a population of over 300,000 people. We look forward to seeing you in Warri for a stimulating and enjoyable conference. Kindest regards,

Prof. Mohammed Kaoje Abubakar8 for the organizing committee.

Useful comparative analysis of sequence classification systems w/ a few questionable bits

noreply@blogger.com (Jonathan Eisen) — Tue, 15 May 2012 07:09:00 +0000

There is a useful new publication just out: BMC Bioinformatics | Abstract | A comparative evaluation of sequence classification programs by Adam L Bazinet and Michael P Cummings. In the paper the authors attempt to do a systematic comparison of tools for classifying DNA sequences according to the taxonomy of the organism from which they come.

I have been interested in such activities since, well, since 1989 when I started working in Colleen Cavanaugh's lab at Harvard sequencing rRNA genes to do classification. And I have known one of the authors, Michael Cummings for almost as long.

Their abstract does a decent job of summing up what they did

Background
A fundamental problem in modern genomics is to taxonomically or functionally classify DNA sequence fragments derived from environmental sampling (i.e., metagenomics). Several different methods have been proposed for doing this effectively and efficiently, and many have been implemented in software. In addition to varying their basic algorithmic approach to classification, some methods screen sequence reads for ’barcoding genes’ like 16S rRNA, or various types of protein-coding genes. Due to the sheer number and complexity of methods, it can be difficult for a researcher to choose one that is well-suited for a particular analysis.

Results
We divided the very large number of programs that have been released in recent years for solving the sequence classification problem into three main categories based on the general algorithm they use to compare a query sequence against a database of sequences. We also evaluated the performance of the leading programs in each category on data sets whose taxonomic and functional composition is known.

Conclusions
We found significant variability in classification accuracy, precision, and resource consumption of sequence classification programs when used to analyze various metagenomics data sets. However, we observe some general trends and patterns that will be useful to researchers who use sequence classification programs.

The three main categories of methods they identified are

Programs that primarily utilize sequence similarity search
Programs that primarily utilize sequence composition models (like CompostBin from my lab)
Programs that primarily utilize phylogenetic methods (like AMPHORA & STAP from my lab)

The paper has some detailed discussion and comparison of some of the methods in each category. They even made a tree of the methods

Figure 1. Program clustering. A neighbor-joining tree
that clusters the classification programs based on their similar attributes. From here.

In some ways - I love this figure. Since, well, I love trees. But in other ways I really really really do not like it. I don't like it because they use an explicitly phylogenetic method (neighbor joining, which is designed to infer phylogenetic trees and not to simply cluster entities by their similarity) to cluster entities that do not have a phylogenetic history. Why use neighbor-joining here? What is the basis for using this method to cluster methods? It is cute, sure. But I don't get it. What do deep branches represent in this case? It drives me a bit crazy when people throw a method designed to represent branching history at a situation where clustering by similarity is needed. Similarly it drives me crazy when similarity based clustering methods are used when history is needed.

Not to take away from the paper too much since this is definitely worth a read for those working on methods to classify sequences as well as for those using such methods. They even go so far as to test various web served (e.g., MGRAST) and discuss time to get results. They also test the methods for their precision and sensitivity. Very useful bits of information here.

So - overall I like the paper. But one other thing in here sits in my craw in the wrong way. The discussion of "marker genes." Below is some of the introductory text on the topic. I have labelled some bits I do not like too much:

It is important to note that some supervised learning methods will only classify sequences that contain “marker genes”. Marker genes are ideally present in all organisms, and have a relatively high mutation rate that produces significant variation between species. The use of marker genes to classify organisms is commonly known as DNA barcoding. The 16S rRNA gene has been used to greatest effect for this purpose in the microbial world (green genes [6], RDP [7]). For animals, the mitochondrial COI gene is popular [8], and for plants the chloroplast genes rbcL and matK have been used [9]. Other strategies have been proposed, such as the use of protein-coding genes that are universal, occur only once per genome (as opposed to 16S rRNA genes that can vary in copy number), and are rarely horizontally transferred [10]. Marker gene databases and their constitutive multiple alignments and phylogenies are usually carefully curated, so taxonomic and functional assignments based on marker genes are likely to show gains in both accuracy and speed over methods that analyze input sequences less discriminately. However, if the sequencing was not specially targeted [11], reads that contain marker genes may only account for a small percentage of a metagenomic sample.

I think I will just leave these highlighted sections uncommented upon and leave it to people to imagine what I don't like about them .. for now.

Anyway - again - the paper is worth checking out. And if you want to know more about methods used for classifying sequences see this Mendeley collection which focuses on metagenomic analysis but has many additional paper on top of the ones discussed in this paper.

Interesting new paper: "Proving universal common ancestry with similar sequences"

noreply@blogger.com (Jonathan Eisen) — Tue, 15 May 2012 01:25:00 +0000

Just discovered an interesting paper by Leonardo de Oliveira Martins and David Posada. It is titled "Proving universal common ancestry with similar sequences." It relates to a paper by Douglas Theobald: "A formal test of the theory of universal common ancestry. Nature 2010; 465:219-22." Although the latter paper is not openly available the more recent one is.

The new paper is worth a look. Not sure about the Theobald one as I do not have access from home.

Am hoping Leonardo writes more about this in his blog: Bayesian Procedures in Biology ....

Mini post: Microbial forensics

noreply@blogger.com (Jonathan Eisen) — Sat, 12 May 2012 17:51:00 +0000

A few months old here but there is a very interesting post from the Science Media Centre in New Zealand: Science Media Centre: Microbes in soil could help fight crime. The post describes attempts to use microbes in soil as part of forensic activities. This relates in many ways to my call for a "Field Guide to Microbes".

I have been interested in microbial forensics for many years since I worked at TIGR on part of the project to study anthrax genomes. For those interested in microbe-related forensic activities I have created a Mendeley collection of references on the topic.

Microbial Forensics is a group in Biological Sciences, Law on Mendeley.

Oh the irony - new #OpenAccess #PLoSOne paper on Research Blogs doesn't share data behind analyses.

noreply@blogger.com (Jonathan Eisen) — Sat, 12 May 2012 07:24:00 +0000

Interesting new paper: PLoS ONE: Research Blogs and the Discussion of Scholarly Information. All about the new world of science blogging. Much of the context here relates to openness. Yet as far as I can tell, the data collected that make up the meat of the analyses in the paper, are not shared. Uggh.

Is there something I am missing here? Shouldn't a prerequisite of publishing this kind of paper be sharing the information / data used in the analyses? Shouldn't that be released with the paper?

Definitely time to start "Open Data Watch" where people have a place to complain about lack of open availability of data behind papers (I came up with the name as a mimic of Ivan Oransky's diverse watch sites like Retraction Watch). Originally in thinking about doing this I had been thinking about genomic data. But I am sure this is a problem in other areas. Consider paleontology, where openness to fossils and other samples is, well, not as common as it should be. It is not that hard anymore to find a place to share one's data. With places like Data Dryad and Biotorrents and FigShare and Merritt and 100s of others it is really inexcusable not to share the data behind a paper in most cases. Certainly, in some cases there maybe privacy issues but that is not the case here (I think) and not an issue in most cases.

Come on people. If scientific papers are to be reproducible and testable, you need to give people access to the data you used. Shema, H., Bar-Ilan, J., & Thelwall, M. (2012). Research Blogs and the Discussion of Scholarly Information PLoS ONE, 7 (5) DOI: 10.1371/journal.pone.0035869

'Danger and Evolution in the Twilight Zone': Guest post by Randen Patterson and Gaurav Bhardwaj

noreply@blogger.com (Jonathan Eisen) — Fri, 11 May 2012 14:43:00 +0000

Figure 1. PHYRN concept and work flow.

'Danger and Evolution in the twilight zone'

I have been communicating with Randen Patterson on and off over the last five years or so about his efforts to try and study the evolution of gene families when the sequence similarity in the gene family is so low that making multiple sequence alignments are very difficult. Recently, Randen moved to UC Davis so I have been talking / emailing with jim more and more about this issue. Of note, Randen has a new paper in PLoS One about this topic: Bhardwaj G, Ko KD, Hong Y, Zhang Z, Ho NL, et al. (2012) PHYRN: A Robust Method for Phylogenetic Analysis of Highly Divergent Sequences. PLoS ONE 7(4): e34261. doi:10.1371/journal.pone.0034261.

Figure 8. Model for the Evolution of the DANGER Superfamily.

I invited Randen and the first author Gaurav Bhardwaj to do a guest post here providing some of the story behind their paper for my ongoing series on this topic. I note - if you have published an open access paper on some topic related to this blog I would love to have a guest post from you too. I note - I personally love the fact that they used the "DANGER" family as an example to test their method.

Here is their guest post:

A fundamental problem to phylogenetic inference in the “twilight zone” (<25% pairwise identity), let alone the “midnight zone” (<12% pairwise identity), is the inability to accurately assign evolutionary relationships at these levels of divergence with statistical confidence. This lack of resolution arises from difficulties in separating the phylogenetic signal from the random noise at these levels of divergence. This obviously and ultimately stymies all attempts to truly resolve the Tree of Life. Since most attempts at phylogenetic inferences in twilight/midnight zone have relied on MSA, and with no clear answer on the best phylogenetic methods to resolve protein families in twilight/midnight zone, we have presented rest of this blog post as two questions representative of these problems.

Question1: Is MSA required for accurate phylogenetic inference?

Our Opinion: MSA is an excellent tool for the inference from conserved data sets, but it has been shown by others and us, that the quality of MSA degrades rapidly in the twilight zone. Further, the quest for an optimal MSA becomes increasingly difficult with increased number of taxa under study. Although, quality of MSA methods has improved in last two decades, we have not made significant improvements towards overcoming these problems. Multiple groups have also designed alignment-free methods (see Hohl and Ragan, Syst. Biol. 2007), but so far none of these methods has been able to provide better phylogenetic accuracy than MSA+ML methods. We recently published a manuscript in PLoS One entitled “PHYRN: A Robust Method for Phylogenetic Analysis of Highly Divergent Sequences” introducing a hybrid profile-based method. Our approach focuses on measuring phylogenetic signal from homologous biological patterns (functional domains, structural folds, etc), and their subsequent amplification and encoding as phylogenetic profile. Further, we adopt a distance estimation algorithm that is alignment-free, and thus bypasses the need for an optimal MSA. Our benchmarking studies with synthetic (from ROSE and Seqgen) and biological datasets show that PHYRN outperforms other traditional methods (distance, parsimony and Maximum Liklihood), and provides significantly accurate phylogenies even in data sets exhibiting ~8% average pairwise identity. While this still needs to be evaluated in other simulations (varying tree shapes, rates, models), we are convinced that these types of methods do work and deserve further exploration.

Question 2: How can we as a field critically and fairly evaluate phylogenetic methods?

Our Opinion: A similar problem plagued the field of structural biology whereby there were multiple methods for structural predictions, but no clear way of standardizing or evaluating their performance. An additional problem that applies to phylogenetic inference is that, unlike crystal structures of proteins, phylogenies do not have a corresponding “answer” that can be obtained. Synthetic data sets have tried to answer this question to a certain extent by simulating protein evolution and providing true evolutionary histories that can be used for benchmarking. However, these simulations cannot truly replicate biological evolution (e.g. indel distribution, translocations, biologically relevant birth-death models, etc). In our opinion, we need a CASP-like model (solution adopted by our friends in computational structural biology), where same data sets (with true evolutionary history known only to organizers) are inferred by all the research groups, and then submitted for a critical evaluation to the organizers. To convert this thought to reality, we hereby announce CAPE (Critical Assessment of Protein Evolution) for Summer 20132. We are still in pre-production stages, and we welcome any suggestions, comments and inputs about data sets, scoring and evaluating methods.

Bhardwaj, G., Ko, K., Hong, Y., Zhang, Z., Ho, N., Chintapalli, S., Kline, L., Gotlin, M., Hartranft, D., Patterson, M., Dave, F., Smith, E., Holmes, E., Patterson, R., & van Rossum, D. (2012). PHYRN: A Robust Method for Phylogenetic Analysis of Highly Divergent Sequences PLoS ONE, 7 (4) DOI: 10.1371/journal.pone.0034261

Quick post - new paper of interest on "The Infinitely Many Genes Model ..."

noreply@blogger.com (Jonathan Eisen) — Fri, 11 May 2012 03:11:00 +0000

This paper seems of potential interest: The Infinitely Many Genes Model for the Distributed Genome of Bacteria by Franz Baumdicker, Wolfgang R. Hess, and Peter Pfaffelhuber

Abstract:

The distributed genome hypothesis states that the gene pool of a bacterial taxon is much more complex than that found in a single individual genome. However, the possible fitness advantage, why such genomic diversity is maintained, whether this variation is largely adaptive or neutral, and why these distinct individuals can coexist, remains poorly understood. Here, we present the infinitely many genes (IMG) model, which is a quantitative, evolutionary model for the distributed genome. It is based on a genealogy of individual genomes and the possibility of gene gain (from an unbounded reservoir of novel genes, e.g., by horizontal gene transfer from distant taxa) and gene loss, for example, by pseudogenization and deletion of genes, during reproduction. By implementing these mechanisms, the IMG model differs from existing concepts for the distributed genome, which cannot differentiate between neutral evolution and adaptation as drivers of the observed genomic diversity. Using the IMG model, we tested whether the distributed genome of 22 full genomes of picocyanobacteria (Prochlorococcus and Synechococcus) shows signs of adaptation or neutrality. We calculated the effective population size of Prochlorococcus at 1.01 × 1011 and predicted 18 distinct clades for this population, only six of which have been isolated and cultured thus far. We predicted that the Prochlorococcus pangenome contains 57,792 genes and found that the evolution of the distributed genome of Prochlorococcus was possibly neutral, whereas that of Synechococcus and the combined sample shows a clear deviation from neutrality.

Wish they had gone beyond these two cyanobacteria ... but still seems of possible interest. Baumdicker, F., Hess, W., & Pfaffelhuber, P. (2012). The Infinitely Many Genes Model for the Distributed Genome of Bacteria Genome Biology and Evolution, 4 (4), 443-456 DOI: 10.1093/gbe/evs016

Any method allowed for presentations at ASM meeting, as long as you use Powerpoint on a PC.

noreply@blogger.com (Jonathan Eisen) — Wed, 09 May 2012 19:52:00 +0000

Just got this email from ASM linking to a message about my presentation at the upcoming ASM meeting in San Francisco.

Here is the message.

Ugggh.

I highlight some parts that I find disappointing at best. Basically- they say "You can do your presentation is any way. As long as you convert it to PowerPoint for a PC." Never mind other tools to do presentations. Like Keynote. Or Prezi. Or, well, anything else. Never mind people who use Macs. Or Linux computers. Or iPads.

I have NEVER had a problem doing a presentation off of my Mac or iPad. I have had MANY problems when I have converted my Keynote or PDF files or other material to Powerpoint for a PC.

Oh, and forget about modifying your presentation in response to anything going on in the session (which I do frequently). I try to tune my slides to the actual crowd. No longer possible.

Maybe I should use no slides, like I did at TEDMED. Or maybe I should do a Ross Perot and have charts. Maybe I will bring my own projector and set it up just before my talk ... who knows ... but I hate it when meetings say "Trust us - you won't have any problems with our system".

May 9, 2012

Dear Jonathan Eisen;
Thank you for participating as a speaker at asm2012, ASM's 112th General Meeting in San Francisco, June 16-19, 2012. As a speaker, we kindly request that you consider the following guidelines as you finalize your PowerPoint presentation in the session listed below and also take note of some of the new requirements and changes for asm2012.

Session Details
Session Date/Time: 6/17/2012 3:00:00 PM - 6/17/2012 5:30:00 PM
Session Title: The Great Indoors: Recent Advances in the Ecology of Built Environments
Presentation Title: microBEnet: The Microbiology of the Built Environment Network (If your presentation title is not listed or incorrect, please provide this information to xxxxx immediately.
Length of your Personal Presentation: You are allotted 30 minutes for your presentation or lecture unless otherwise notified by the convener of this session.

New this Year
In order to provide the highest quality experience for our attendees, ASM now requires that all speakers upload their presentations at least four hours before their session begins (if you have a morning session, we recommend you upload your slides at 2:00 p.m. the afternoon before).

Speakers will no longer be permitted to use personal laptops during their presentations. The General Meeting began experiencing a greater number of technical issues as more and more speakers relied on using personal laptops from which to present. This contributed to unique technical situations during individual presentations as well as awkward transitions between speakers. The General Meeting will be utilizing the Presentation Management System for all speakers and our talented and dedicated set of technicians will be well-prepared and equipped to ensure all presentations are presented in the way they are intended and there are smooth transitions between speakers.

asm2012 will feature a networked presentation submission system, called our Presentation Management System. The tips below will help ensure that little, if any, editing will need to be done on-site, allowing you to quickly review your presentation and then attend other sessions in progress. However, ASM strongly recommends that you visit the Speaker Ready Room in Room 120 to test your slides before your session begins to ensure that they run properly on the Presentation Management System. The Presentation Management System can accommodate both Mac and PC based presentations.

The tips below are for both Windows and Mac users. As all the provided computers will be PCs, Mac users should additionally review Considerations for Mac Users at the bottom of this document.

· Building Your Presentation

Movies:
Please take steps to compress your videos. Uncompressed videos will take longer to upload and load within your presentation, and will not be better quality than a modern MPEG-4 codec. We can only accept movies created as MPGs, WMVs, or with the following AVI codecs: MPEG-4 (Divx, Xvid, or WMVs), Cinepack, Techsmith. Flash content (SWF) is fully supported.

Note: It is important your movies do not completely fill the screen. In the meeting room you will only have a mouse to advance your slides. You can only advance your PowerPoint with a mouse by clicking on the slide, not the movie itself.

DVDs:
If you plan to play a DVD as part of your presentation, please notify a technician in the Speaker Ready Room so arrangements can be made for assistance in your meeting room.

Fonts:
We only supply fonts that are included with Office 2010. If you need a specialized font, it should be embedded into your PowerPoint presentation. For instructions on this process, please click on the following link: http://support.microsoft.com/kb/826832/en-us

· Before you Depart

Advance Submission:
You may submit your presentation starting on Friday, May 18. You will receive a notification on May 18 that will provide you with the link to upload your presentation.

Multiple Presenters:
Please do not combine multiple presenters’ PowerPoints into one file and then submit under one name. The Presentation Management System manages presenters individually and any co-presenter will not be able to logon to edit the combined presentation.

Backup:
Please bring a backup copy of your presentation along with you when you depart for your meeting. Copy your PowerPoint and all movies to a folder on a USB drive or CD. PowerPoint does NOT embed movies, and therefore, they must all be placed in the same folder as your PowerPoint.

· At the Meeting

Speaker Ready Room:

Speakers should review their presentation in the Speaker Ready Room prior to their scheduled presentation. The Speaker Ready Room will be staffed with technicians that can assist with any compatibility or formatting issues within your presentation. The computers in the Speaker Ready Room will be configured with hardware and software exactly like the computer in the meeting rooms.

Be sure to use the mouse to advance your slides, not the keyboard, as you will only have a mouse at the podium to advance your presentation. Left click advances the slides; right click goes back. Once you are comfortable that your presentation is complete, confirm the date, time, and room for your session. Be sure to click the green “save/logout” button on the top of the screen.

Speaker Ready Room: Room 120

Hours of Operation:

Friday, 6/15/12: 8:00 a.m. – 5:00 p.m.
Saturday, 6/16/12: 7:00 a.m. – 7:00 p.m.
Sunday, 6/17/12: 6:00 a.m. – 7:00 p.m.
Monday, 6/18/12: 6:00 a.m. – 7:00 p.m.
Tuesday, 6/19/12: 6:00 a.m. – 3:00 p.m.

· Considerations for Mac Users

Pictures:
If you use a version of PowerPoint prior to 2008, please be sure any embedded pictures are not TIFF format. These images will not show up in Windows PowerPoint. With PowerPoint 2010 for the Mac, this is no longer an issue, and any inserted image will be compatible.

Keynote Users:
Please export your presentation as a PowerPoint Presentation. If you are having any issues please notify Mac support at XXXXX for additional help.

By following the guidelines above, your presentation will go smoothly. Should you have any questions not addressed in this document, please feel free to email XXXX.

If you have any questions regarding the scientific program or session details, please contact Janet Mitchell at XXXXXX.

Sincerely,

Janet M Mitchell, M.S.
Program Manager, General Meeting

Scholarly Kitchen - getting more and more rotten as the days go by

noreply@blogger.com (Jonathan Eisen) — Wed, 09 May 2012 08:14:00 +0000

In February I wrote about how something smelled funny with the connection between "The Scholarly Kitchen" blog and the Heartland Institute: The Tree of Life: Something rotten in the Scholarly Kitchen? (Climate Change Denialism is Everywhere)

Well, though I thought the Heartland Institute was a bit extreme from the previous "work" it seems they have gone even more off the deep end recently with their ad campaign featuring ~~Charles Manson~~ Ted Kaczynski

This least effort has led to an even further reduction in support for the folks at Heartland. See for example:

And more.

So - amazingly - as Heartland dips more and more into extremism - I have seen no sign from anyone at the Scholarly Kitchen of any concern that one of their co-bloggers - David Wojick - also happens to work for the Heartland Institute:

What does this say about TSK? Not sure. But it continues to smell funny to me. Wojick is using his position at TSK to make him seem like an academic. Heartland is using his seeming academic status to promote their ideas, which get more and more extreme by the day apparently. As even very conservative groups disavow themselves of any affiliation with Heartland, pulling money, and other kinds of support, I still have yet to see any public comments from TSK folks about whether they think Wojick is using his role in their blog to indirectly promote extreme ideas ...

Dueling microbial diversity talks at #UCDavis on May 2 #symbioses #microbiology

noreply@blogger.com (Jonathan Eisen) — Sat, 05 May 2012 20:52:00 +0000

Here is a storification of the dueling microbial diversity talks that happened at UC Davis on Wednesday May 2.

How complete do microbial genomes have to be for metabolic predictions (to be useful)?

noreply@blogger.com (Jonathan Eisen) — Fri, 04 May 2012 21:17:00 +0000

OK. Got a question for the blogo-twitto-webosphere.

In this day an age of rapid shotgun sequencing of genomes, many people are moving away from finishing the genomes. As some may know, I was a co-author many years ago on a paper arguing for the need to finish (rather than just shotgun sequence) microbial genomes for many scientific questions. But as sequencing costs continued to plummet, the relative cost of shotgun sequencing genomes kept going down while the cost of finishing genomes did not change much. So. two years ago I posted to my blog a question regarding this: "Wanted:Feedback on Importance of Finishing (Microbial) Genomes" and got a lot of useful feedback. And eventually, I came around to the argument that finishing was unnecessary for many purposes (and even got some props for admitting I was wrong).

Well, I am back. Now I am arguing to some colleagues that if we want to make metabolic pathway predictions and metabolic models for genomes, we probably don't need finished genomes. But alas, I have no evidence to back that up. And in fact, I am not really sure anyway. So I am asking everyone and anyone out there ... does anyone have data/evidence/opinions about whether there will be much difference in metabolic predictions one would make for an organism based upon a complete genome vs. a shotgun assembly of a genome generated by Illumina sequencing?

Thanks

Storification of some comments:

View the story "Completeness of microbial genomes for metabolic predictions" on Storify

Draft of a Proposal for a UC #OpenAccess policy - comments wanted

noreply@blogger.com (Jonathan Eisen) — Thu, 03 May 2012 22:33:00 +0000

Just got sent this email

Dear Colleagues,

On behalf of the Academic Senate Library Committee (ASLC), I am asking for your comments on the attached proposed Open Access Publishing Policy for the University of California.. All faculty, including Academic Federation members are invited to post their comments on the Academic Senate web-forum site at http://academicsenate.ucdavis.edu/Forums/index.cfm?Forum_ID=67. Please go to this site to submit your feedback.

Briefly, the issue is this: the faculty of the University of California, in conjunction with the University Committee on Libraries and Scholarly Communication (UCOLASC), is proposing a new OPEN ACCESS PUBLISHING POLICY that will apply to the dissemination of all scholarly work. UCOLASC is seeking feedback from all campuses on this issue in order to inform a final version of the policy which will be presented to the Universitywide Academic Senate sometime this calendar year.

The ASLC would appreciate your comments by Wednesday, May 9, 2012. Your ideas will then be shared with UCOLASC in time for its May 25th meeting. The web-forum will remain open substantially past May 9, and we will endeavor to include as many comments up to May 25 as possible.

Sincerely,

Brian H. Kolner

Academic Senate Library Committee

The relate to a draft of a proposal for a new Open Access Publishing Policy being circulated at the University of California. The draft of the proposal can be found here.

UC Davis (and I presume other UCs) are now soliciting comments on the proposal. I would love to here / read comments from anyone. Personally, I think the policy is way to weak as it allows exceptions to be granted ...