genophoria

Genomics euphoria: ramblings of a scientist on genetics, genomics and the meaning of life

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Greetings from UCSF

As of May 1st, I have started as an Assistant Professor at UCSF, Department of Biochemistry and Biophysics. I am also affiliated with the Department of Urology and the Helen Diller Family Comprehensive Cancer Center. The switch from postdoc to assistant professor has been daunting and at times overwhelming, but overall I am excited about starting this new chapter in my career. My home departments are filled with amazing scientists, some of whom have been my long-time heroes. I feel supported and fortunate to be where I am and to have the opportunities that I have. There is a lot on the scientific front that I want to write about that will show up in the near future on this blog. But for now, I wanted to keep this announcement short. Please visit our labpage at goodarzilab.org and feel free to contact us should the need arise. As we are building our group, we are always looking for smart students and postdocs who would like to be part of our team as we try to build a multidisciplinary group worthy of 21st century science.

How to run kallisto on NCBI SRA RNA-Seq data for differential expression using the mac terminal

Very useful post on Kallisto.

Andrew T McKenzie

Attention Conservation Notice: This post explains how to run the exceptionally fast RNA-seq k-mer aligner kallisto from the Pachter lab on data you download from NCBI’s Short Read Archive, and then analyze it for differential expression using voom/limma. As with everything in bioinformatics, this will likely be obsolete in months, if not weeks.


Kallisto is really fast and non-memory intensive, without sacrificing accuracy (at least, according to their paper), and therefore has the potential to make your life a lot easier when it comes to analyzing RNA-seq data.

As a test data set, I used the very useful SRA DNA Nexus to search the SRA database for a transcriptome study from human samples with 2-3 biological replicates in 2 groups, so that I could achieve more robust differential expression calls without having to download too much data.

I ended up using SRP006900, which is titled “RNA-seq of two…

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The two cultures of mathematics and biology

An excellent take on interdisciplinary research at the intersection of math and biology!

Bits of DNA

I’m a (50%) professor of mathematics and (50%) professor of molecular & cell biology at UC Berkeley. There have been plenty of days when I have spent the working hours with biologists and then gone off at night with some mathematicians. I mean that literally. I have had, of course, intimate friends among both biologists and mathematicians. I think it is through living among these groups and much more, I think, through moving regularly from one to the other and back again that I have become occupied with the problem that I’ve christened to myself as the ‘two cultures’. For constantly I feel that I am moving among two groups- comparable in intelligence, identical in race, not grossly different in social origin, earning about the same incomes, who have almost ceased to communicate at all, who in intellectual, moral and psychological climate have so little in common that instead of crossing the campus…

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Confessions of a bad writer

“One day I will find the right words, and they will be simple.” –Jack Kerouac

I am a bad writer! And a piece by Steven Pinker in chronicles of higher education made me feel awful about it. I recommend that you read it too… and I’m sure you will feel self-conscious about your writing as well. I even went back and checked some of my papers. Examples cited by Steven Pinker are aptly chosen and I’ve come by many such convoluted verbiage myself in my day-to-day readings. For example:

The methods section of an experimental paper explains, “Participants read assertions whose veracity was either affirmed or denied by the subsequent presentation of an assessment word.” After some detective work, I determined that it meant, “Participants read sentences, each followed by the word true or false.” The original academese was not as concise, accurate, or scientific as the plain English translation.

To be fair, I know scientists who write with an enviable clarity. My PhD advisor, Saeed Tavazoie, is one of those academics. The ease with which he finds the right adjectives and adverbs, even in the context of a casual conversation about his scientific ideas, has always baffled me. More importantly, I believe that the ability to deconstruct a complex notion into parts that can be simply conveyed is a measure of true understanding of scientific matter. Unfortunately, I’m not one of those scientists… at least not yet.

cjdno

Your writing is bad, and you should feel bad… Dr. Zoidberg is judging you!

There is one point, however, that I think should be discussed. Scientists publish two kinds of scientific material, on the one hand we write papers usually aimed at scientists in our own field (or even sub-field and sub-sub-field); on the other hand, we write blog posts, perspectives, insights, reviews and etc. The latter is meant for a broad audience and should be amply clear to everyone with or without expertise. There are no arguments there. However, when it comes to papers, I’m not 100% sure that writing for a broad audience should be our main goal… I don’t think it should even be on the list at all. I’m not talking about clarity, rather, I’m talking about assuming a broad readership. For example, Steven Pinker writes:

“A considerate writer will also cultivate the habit of adding a few words of explanation to common technical terms, as in “Arabidopsis, a flowering mustard plant,” rather than the bare “Arabidopsis” (which I’ve seen in many science papers).”

My argument is that writing a paper for a broad audience may create a false sense of comprehension. For example, if someone doesn’t know what Arabidopsis is, they should not be reading the text in the first place. Words like significantinformativeassociation, sufficientcausal and … have specific scientific and mathematical meanings that are distinctly different from their everyday use. Not knowing the scientific context in which these words are used, will clearly change our understanding of the text. While academics should absolutely engage in popular science writing, I don’t think scientific papers are the right medium for this endeavor. We as scientists may even want to use the language of the abstract to set a bar for who should be reading the paper in the first place. Public media is rife with examples were non-experts feel they have understood the subject matter in cases where they clearly have not. How many times have we discussed the misuse of “correlation” versus “causation” by the media originating from poor understanding of a published paper.

Again, I’m not talking about convoluted writing here, but rather technical writing. For example, as part of the qualification exams for my PhD candidacy, I was assigned a paper from Bernhard Palsson’s group. The abstract has phrases like “constraints-based in silico models have been used to calculate optimal growth rates” or “incorrect predictions of in silico models based on optimal performance criteria”. I was completely baffled by the text and I couldn’t even begin to understand  the problem the authors were trying to address (you can try this yourself by reading the abstract). It was after reading many MANY papers from this field that I began to understand the language and with that the science behind it. In other words, comprehending the language is serving as a gauge for the ability to understand the science behind it with minimal risk of unintended misunderstandings. As JRR Tolkien wrote, at the Doors of Durin, you should be able to speak friend to enter… scientific papers, akin to mines of moria, are dangerous territories.

Should you do another postdoc?

A good read…

zinemin's random thoughts

Here is yet another article about the negative effect that having to do 2-3 postdocs before being able to apply for tenure-track positions has on people’s life, which has been widely shared and discussed on my facebook.

I left academia after 2 postdocs only 3 months ago, but already now I feel a greater clarity is coming over me regarding the topic. People are forever questioning themselves whether the postdoc lifestyle is still worth it for them or whether they should leave. I have asked myself the same question for 6 years almost every day.

Now I think the situation is much, much simpler than I thought.

In truth, there are only two reasons why you should not quit your postdoc tomorrow and find another job:

(i) You like living abroad and having to change country every 2-3 years. You think this lifestyle has clear advantages to living in one…

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In situ genotyping

We have glimpsed the future of genetics and it is colorful

Two papers showed up in the last issue of Nature methods that caught my attention:  I mean Levsesque et al of U Penn and Ke et al. from Stockholm University. I’m generally biased towards methods papers and I find them WAY more interesting than your run-of-the-mill biology papers. But why these two papers? I have a conviction… I say conviction because until now there was very little to back it up: the future of biology rests not just in our understanding the populations of cells and observing the “average” phenotypes/phenotypes, but rather a single-cell approach is required to understand all the complex dynamics upon which biological systems thrive. FIrst came single-cell sequencing… then came single-cell barcoded RNA-seq… and now single-cell in situ genotyping/sequencing is here.

There is a magic to watching cells shine under a microscope… there is a feeling of vindication… of assurance. But it is not just that. A cell is already an “average”; an average of paternal and maternal genetic information. And FISH-based methods enable us to distinguish between them. More importantly, in addition to quantity (which to be fair is not its strongest suit), we get a feel for localization in different compartments.

Granted I’ve never done a FISH experiment. So I really don’t know how much of this is real and how much of it cherry-picking. But I’m sure if we can get there, it will be illuminating. And I don’t mean that we should drop the population for single-cells… I think we’ll be in for a surprise. I think we’ll understand, at last, how stupid a single cell is. We’ll know that individual cells make a lot of mistakes and it is the averaging effect of a population that results in a coherent behavior. In other words, I’m not interested in studying single-cells per se, but rather I want to know about them so that I can have smarter models of a population. The same way a thought forms in our brains despite many erratic firings of individual neurons, I want to know how stable phenotypes emerge in spite of, not because of, single-cell variations. Only then we’ll know which pathways are consistently crucial for a single cell and which ones are meaningful only in the context of a population.

Genophoria returns

As it’s probably obvious to the two people who follow my blog, I’ve been on a sort of hiatus. I’be been nursing a torn TFCC with significant debilitating effects on my ability to work/write. Which reminds me… watch out for that pesky lid on your liquid N2 storage units (you think they’ll stay up, but sometimes they won’t). But as my range of motion and quality of life increases, I’m planning my way back to writing about things that I find interesting in the forefronts of science.

A lot has happened since I was gone:

  1. CISPRs: I wrote about the CRISPR/CAS system a while back and now they’re everywhere… with a vengeance! Multiplexed genome targeting of various genomes (including stem cells), guide-RNA mediated gene silencing, and other exciting tools. There are even companies starting to sell these products as evident in my targeted ads on various journal home-pages. I’m sure this is just the beginning… a lot more is coming.
  2. RNA elements: At last the first compendium of sequences bound by various RNA-binding protein was published. It’s in-vitro and limited but still… it’s a huge deal! I’m even more excited because my dear friend Hamed was the fifth co-first author on that paper (yes… there is such thing as 5th co-first author).
  3. Cancer research: there is no shortage of papers (great or otherwise) published on the subject of cancer/cancer metastasis. But it’s not every day that our lab is involved in major steps forward. Well… it may be every day but people have to actually wait until they come out.
  4. And many other things: I had flagged many papers to write about but to be honest a lot of them have lost their “it” factor at this point. I’ll write about some of them in an up-coming post very soon.

Reviewing the “peers”

A while back, with some not too complex detective work on the part of USA Today, we got our hands on the reviewer comments from the infamous #arseniclife paper. Looking at the reviews, I agreed with the experts, including Leonid Kruglyak, who “reviewed the reviews”, that they generally looked normal… yes, they were quite positive at times but let’s face it, some scientists are nice and some aren’t and by chance alone, you might have a group of three that use encouraging words even if there are criticisms. But since then, I’ve seen opinions written out there that are not too kind to these reviewers… good thing they’re anonymous, or we were looking for our pitchforks now! Even Ash Jogalekar over at “The Curious Wavefunction“, whose posts I often find refreshing, called the reviewers out on their subpar job.

But what do “I” think about this whole fiasco? I think hindsight is 20/20… It all comes down to taking the authors at their word that there was no phosphorus in the media they used… everything else follows… But as it turns out, that is very difficult to achieve. But I didn’t know that and if I was a reviewer, I wouldn’t have brought it up either. I probably would’ve asked for specific experiments but they would be based on my background (and could be claimed to be “outside the scope”). And that is all it comes down to, isn’t it? Our backgrounds… and the reviewers are in fact chosen from different areas. For a paper like this, you probably will get a bacteriologist, may be someone working on Archea and maybe a chemist would not even be on the short list (let alone one that would have the relevant knowledge). In the end of the day, I don’t think that as researchers, we want reviewers to be too ambitious… we have all got bad reviews that we think are nonsensical. I actually think the reviewers should just make sure, given the facts and their knowledge, the results are not seriously flawed. And we all know that a published paper is not exactly the word of God and it can be easily refuted/corrected/expanded upon.

So, if we all know these things, then what is the source of the outrage? I think there are a number of points:

  1. This is Science we are talking about here… we like to think that the impact factor of the journal has a strong correlation to the strength of its underlying science. We all toil away for years hoping to get a paper in Science and it breaks our heart to see a flawed paper like this appear on its pages. I agree that this paper, in retrospect, is outrageous but this is not the first time a bad paper is published in Science or Nature or any other journal.
  2. This process shows every thing that’s wrong in research nowadays… holding press conferences like a true salesman, relying on seemingly random reviews to accept a paper and the disproportionate value associated to papers in big name journals.

Are there solutions to these problems? Of course there are… pretty old ones actually. Switching to Arxive model instead of the journal model makes a lot of sense… in that model, studies are presented on equal footing and it is on their own merit that they gain attraction. Can we ever do that? Not in the near future… biology is expensive and researchers need decent publications for every grant cycle. We simply don’t have the luxury of time to wait for our papers to climb the citation ladder (that is assuming citation is even a good measure of merit). The current journal structure enables us to “assign” a “value” to a paper based on a couple of samplings, even before the paper is published. Is it a flawed process? Of course. Is it at times unfair? Absolutely. But let’s realize what the problem is: just too many people, not enough money. Let’s not heap all that on the shoulders of three reviewers…

The rise of “entertainment-science”

I wanted to write about the very interesting back to back Cell papers of c-myc (this and this). But at the last second, I changed my mind. I want to write, instead, about what people have been writing about all week… that is the paper by French scientist attacking the safety of genetically modified food. Genetically modified organisms are crops and animals that have been genetically engineered to improve their efficiency and productivity, from pest-resistance to higher milk productions. They have been around for sometime now and despite countless studies, there is very little evidence threatening the safety of the whole category…

The controversy, however, is alive and kicking and the Seralini et al paper drops the hammer on the safety of GM maize. I don’t want to talk about the short-comings of this paper, you can get that from other sources (e.g. here and here). Instead, I want to talk about a broader phenomenon, the rise of entertainment value in controversial science:

  1. I am sure there are many world-class scientists who focus on GM-food safety. But I don’t know any of them, do I? Instead, I and many like me (who read science news) know Seralini, mainly because his papers are always controversial and go against the consensus of the field. There is nothing inherently wrong with that… but I think amazing claims require amazing accompanying evidence. It is OK when papers show up that go against the norm… either the whole field is wrong (which sometimes happens) or there is something wrong with that study (which happens quite often, case in point: faster than light neutrinos). But what I think is weird, is that these studies get WAY more publicity than they should. And in the end of the day, it makes us scientists look bad. People hear about all these extraordinary findings that are then debunked in a couple of months… no wonder we have problems with the perception of science in public.
  2. From linking disease to vaccination to discovering a new Arsenic-based form of life, we have let science down again and again… not by making mistakes. Being wrong is fine, it is the first step towards getting it right, but rather through pushing our results into the spotlight. Holding press conferences, enforcing gag orders on collaborators and pulling off all the PR stops. I assume, soon we’ll see trailers of upcoming publications on TV (“…starring POLR2A as RNA polymerase II”) with entertaining twists of course.

The majority of science is still working the way it should, but that is not the part we read about in science news sections. I want to think scientists are better than this PR stuff… We were supposed to be skeptics, we were supposed to be above this… we were supposed to be living in our ivory towers. We shouldn’t care about the results of our experiments (positive or negative), we are supposed to be searching for truth… or so I thought.