AMA for fun.

I’ve been asked by a few people to do an AMA, since I seem to be one of the few PhD-level Bioinformaticians working in industry who are active on the Reddit bioinformatics forum.  There are probably a lot of others, but I suspect that the bulk of people there are mostly graduate students or academics.

Anyhow, If anyone is interested in such silliness, here’s the link.

Of course, I’m going to feel pretty silly about the whole thing if no one asks any questions…

The glamour of Pipeline bioinformatics

I’m going to have to eat a bit of humble pie.  When I was a grad student, I may have just slightly looked down on “pipeline bioinformatics”, thinking it was a subject that was boring.  It clearly wasn’t as glamorous as designing new algorithms or plucking hidden bits of information out of giant data sets… I may have even thought it was something you just did as an after thought.

I was wrong.

I have to admit, now that I’ve had a taste of it, I’m enjoying it for exactly the opposite reasons:  It’s a fascinating game of balancing everything you know about computers and biology all at the same time, while making sure you get the right answer consistently.  It’s a cross between doing jigsaw puzzles and playing jeopardy…  and I’m kinda liking it.

In order to build a good pipeline, you need infrastructure that glues all the parts together, you need planning to make sure that it has room for growth, and you need to know what constraints the pipeline will face…  And, you need to be able to understand how everything from the bits of data you’re pushing through it will interact with all of the hardware on all of the machines and wires it’s going to run on.  That’s no small feat – but it’s an exhilarating challenge.

While I may have thought algorithm design was the cat’s pyjamas, building a pipeline is the same resource management challenge scaled up to include a whole lot more moving parts.  And, to those who manage all of those working parts, I finally grok what it is that drives you – and I am only working on a pipeline that was assembled by others, not even one of my own creation – which just increases my respect for those who have built pipelines out of nothing:

The thrill of watching data cascade through the waterfall that is the pipeline.

The excitement of having each individual piece operating in harmony, squeezing out that last bit of performance.

The fun of adding in three more pieces you thought would never fit, but making it work.

The satisfaction of knowing you managed to tame the mangy electrons that seemed so unruly before they entered your pipeline.

The reward of having someone look at the data afterwords, and learning something new from it.

Yes, pipeline bioinformaticians, I owe you an apology, your product is a magnificent work of art in it’s own right – and it is only truly completed when people are able to forget that it’s there. Cheers to you!


How do you become a bioinformatician?

I’ve been following the bioinformatics sub-reddit for the past couple of months, ever since I stumbled upon it when a colleague asked me about bioinformatics resources on the web.  It’s a fascinating place to visit, but it’s incredibly repetitive in that people keep asking “How do I become a bioinformatician?”

Unfortunately there is not a single answer, because bioinformatics isn’t a single job – it’s a collection of people who have found a way to live with one foot in each of two worlds: computer programming and biology.  Getting a firm footing in each can be a serious challenge, as people spend years studying just one of those to become proficient at it.

However, I think there are some common threads that tie the field together.  You need to invest the time in at least a handful of basic fields: some basic programming, some elementary cell biology and at least a simple understanding of math or statistics.  What you can accomplish with just that little can be incredibly productive.  Mostly in terms of automation of data processing or modelling of your results.

On the other hand, bioinformatics also includes a lot of sub-disciplines.  Great programmers can build incredible pipelines.  Great mathematicians can invent or apply algorithms to create new ways of interpreting data, and great biologists can develop heuristics and re-interpret data in new ways to generate insights that others have overlooked.  There’s even room for “neat freaks” in organizing and imposing order on unruly data.

The challenge of becoming a bioinformatician is learning where your strengths and weaknesses lay, and using them to your advantage.  Finding a research group that shores up your weaknesses – or helps you fill them in – can be a great boost to your career.  After my masters degree, I felt I had two big gaping holes in my resume: big data and databases, which I made the focus of my PhD research. Coming out of my defence, I felt I was able to bring a more balanced approach to the table – and had simultaneously purged any instinct I might have ever had to reach for a spreadsheet to interpret information. (Spreadsheets and big data don’t mix.)

So, where does that lead an aspiring bioinformatician?  Unless you take the time to do both a computer science degree and a biology degree, you probably won’t be able to shoehorn everything in to become an expert in both, and not everyone wants to get their PhD to fill in the gaps left in an undergrad education.

With that said, let me lay down a few useful points:

  1. Pick and chose to study subjects that interest you because you’ll at least end up with strengths in things you enjoy, which leads to jobs doing things you enjoy.
  2. You can always learn something new later… but take opportunities to try new things when they come.
  3. Remember that you’re not going to be the expert in every field you put your foot into – so look for opportunities to collaborate with the people who are.  (If you’re going into bioinformatics and expect to do everything yourself, you’re probably doing it wrong.)
  4. Don’t be afraid of the fact that you don’t know stuff.  Your job isn’t to be the best biologist and best computer scientist at the same time – it’s to be the bridge between.  The stronger your foundations, the better a bridge you can be, but unlike a concrete bridge, you can always invest in learning more.
  5. Yes, higher education does help in this field.  Bioinformatics is still dominated by research based organizations, and the academic hierarchy saturates the mindset of bioinformaticians everywhere.  (Or, almost everywhere.)
  6. Bioinformatics is also about the “soft” skills.  Don’t forget that bioinformaticians are also in a good place to be good leaders – since you’ll be one of the few people who can speak both languages, and tie together groups that would otherwise lack a common language.
  7. Don’t believe the hype about what you should learn:  R isn’t really the only language for doing bioinformatics.  Perl isn’t always evil (just most of the time, though it did save the human genome…), Java isn’t the slowest language out there, and c isn’t only for hardcore programmers. (Python, though, is a pretty good all-around language.)  Everyone has an opinion on where bioinformatics is going – but it’s just an opinion, so make your own choices.

At the end of the day, I always give students the same piece of advice:  As you go through life, you will learn new skills that you can apply as you see fit.  At the end of the day, each of these skills will be a tool in your toolbox that you can turn to when you hit a problem.  If you only have a hammer in your toolbox, your repertoire is pretty limited.  On the other hand, if you collect a fantastic assembly of tools, you’ll be equipped to handle just about anything that comes your way.  Your job is to invest your time into building the best toolkit you can, so that when you get out of school, you’ll be ready to solve as many problems as you can.

Bioinformatics is just a special case of toolbox building, in that you need the tools of at least two disciplines in your toolbox.  What you chose to put into your toolbox is entirely up to you, but (to stretch the toolbox analogy just a little too far), take a few minutes to ask if you’d like to be a plumber or a carpenter before you start collecting your tools. Or, without the metaphoric toolkit, ask yourself what kind of bioinformatician you want to be.

Once you know the answer to that question, you’ll figure out pretty quickly which tools you want to start collecting.  And the path towards becoming a bioinformatician will start to become clear.  It may not take you where you expect, but I can guarantee that you’ll be walking down an interesting road.

American Hospitals

This is probably not an informative post for most people who’ve visited my blog, but I thought I’d share a perspective.

Last week, I signed up for a health care plan, and discovered that the plan to which I’d signed up was offering free flu shots.  Not being one to pass up on an offer like that, I traipsed down to the local hospital’s paediatric division, to get my daughter ready for the flu season, with a scheduled stop at the adult clinic just down the street on the way home.

Upon arrival, it turned out that the whole family could get our shots at once, saving us a trip across the park to the adult shot clinic – a nice bonus for us.  Anyhow, once the forms were filled out, and the (now expected) confusion about the existence of people without social security numbers was sorted out, the deed was done. (And, I might add that the woman who did it was exceptional – I barely noticed the shot, and my 2 year old daughter looked at the woman and said “Ow…” before promptly forgetting all about it and enjoying the quickly offered princess sticker.  “Princess Sticker!!!”)

In any case, the real story is what happened after – although it was as much a non-event as the actual shot.  We walked back home, taking a short cut through one of the hostpital’s other buildings.  It was new, it was shiny and it was pimped out.  It looked like the set of Grey’s Anatomy or the set of a Holywood sponsored action movie that will shortly be blown into a million pieces by several action heroes.  I half expected the counters to glint and glitter like a cleaning product commercial.

But, it was also, in a way, surreal.  That hospital doesn’t exist to cure people, or to as a place of healing – or even to do research.  Unlike a Canadian hospital, which is the bulk of my experience with hospitals (although I did visit Danish hospitals disproportionately more than you might think for the length of time I was there), the whole building, it’s contents and it’s staff are all there to turn a profit.

It’s not a tangible difference, but it makes you think about the built in drug stores and cafeterias and posters advertising drugs in a slightly different light.

Why are they promoting that drug?  Would that security guard kick me out if he knew I didn’t have my ID card yet?  Is that doctor running down the hall just trying to cram in as many patients as possible?

It’s strange, because superficially, the hospital isn’t any different than a Canadian hospital (other than being newer than any I’ve ever visited, and the ever present posters advertising drugs, of course), and yet it’s function is different.  It’s roughly the difference between visiting a community centre and a country club.  In any other country in the western world, a hospital is open to all members of the community, whereas the hospitals here require a membership.  It’s just hard not to see it through the Canadian lens, which tells us it’s one of those things American’s “just can’t seem to get right.” Well, that’s the Canadian narrative – whether it’s right or wrong.

Anyhow, a hospital is a hospital: the net product of the hospital is keeping people healthy.  Whether it’s for profit or government run, it does the same things and works the same way.

At the end of the day, I can’t say anything other than that the experience was pleasant, and this is the first year that I’ve gotten a flu shot and didn’t get sick immediately afterwards.  So really, all in all, I guess you get what you pay for…  It’s just a new experience to see such a direct connection between the money and the services.

I just have to wonder how Americans see Canadian hospitals. (-:

Ikea furniture and bioinformatics.

I’ll just come out and say it:  I love building Ikea furniture.  I know that sounds strange, but it truly amuses me and makes me happy.  I could probably do it every day for a year and be content.

I realized, while putting together a beautiful wooden FÖRHÖJA kitchen cart, that there is a good reason for it: because it’s the exact opposite of everything I do in my work.  Don’t get me wrong – I love my work, but sometimes you just need to step away from what you do and switch things up.

When you build ikea furniture, you know exactly what the end result will be.  You know what it will look like, you’ve seen an example in the showroom and you know all of the pieces that will go into putting it together.  Beyond that, you know that all the pieces you need will be in the box, and you know that someone, probably in Sweden, has taken the time to make sure that all of the pieces fit together and that it is not only possible to build whatever it is you’re assembling, but that you probably won’t damage your knuckles putting it together because something just isn’t quite aligned correctly.

Bioinformatics is nearly always the opposite.  You don’t know what the end result will be, you probably will hit at least three things no one else has ever tried, and you may or may not achieve a result that resembles what you expected.  Research and development are often fraught with traps that can snare even the best scientists.

But getting back to my epiphany, I realized that now and then, it’s really nice to know what the outcome of a project should be, and that you will be successful at it, before you start it.  Sometimes it’s just comforting to know that everything will fit together, right out of the box.

I’m looking forward to putting together a dresser tomorrow.

Biking in Oakland

I am slowly feeling like I have more to write, but today, I have a rant.  What the heck is up with Oakland cyclists?

Perhaps I’m just used to Vancouver cyclists, but I’ve never seen a group of people with less regard for the rules of the road.  I always thought drivers who complain about cyclists were just being whiney jerks…  but after 1 week of biking in Oakland, I’m starting to complain about cyclists.

Oddly enough, I think I’m the only cyclist who actually waits for lights to turn green before crossing intersections.  (Though I did go through a red light the other day, when I misunderstood a signal… mea culpa.)  I’m definitely the only cyclist in the city that signals before turning or changing lanes – and probably the only cyclist that isn’t aggressively swerving in and out of traffic!  (I think I’ve seen one other person, but she was going really slow and holding up a line of cars instead.)

Clearly, the insanity is not constrained to cyclists, however.  My wife was yelled at, inexplicably, for coming to a complete stop at a 4-way stop, because apparently that meant she was giving up her right of way.  It was hard to tell, really, as the woman who was yelling tried to cut us off, scream out her window at us, and ignore her own stop sign at the same time.  Oakland is clearly a culture in flux, and I have much to learn, yet, about how to stay safe on the road!

A bit of blogging

I’m more or less sure everyone has forgotten this blog by now… but that’s not a bad thing, really.   I don’t think I had much to say, and life has had a way of keeping me busy. Papers, work, changing work, changing diapers, all of it somehow keeps you from getting a lot of sleep, and that keeps me from having the motivation to write much.

However, I thought I’d start jotting down a few things that are interesting, as I come across them.  One that I’ve recently discovered is that reddit has a bioinformatics subreddit. (, which has been been inspiring me to start writing again.

The other, is that I’ve learned a LOT about mongodb recently, which I would like to start writing about.  Mostly under the “lessons learned” category, because scale up on software is just like scale up in the lab – it doesn’t just work.  Scaling things is tough.

Otherwise, I have a move to Oakland coming up, and there will probably be a few Goodbye Vancouver/Hello Oakland posts as well.  Somehow, I think the urge to write is coming back, and I haven’t had that spark since Denmark ripped it out of me.  Perhaps that’s just a bit of optimism coming back.  I would’t object to that.

On to Omicia!

I’ve dropped a few hints about where I’m headed, recently.  I left a pretty awesome lab at the CMMT last week to join a small company that most people have probably never heard of.  Yes, I still owe the Kobor Lab a final blog post, and have 2 publications in preparation going at the moment, so I guess I haven’t completely left yet, but as of tomorrow morning, I’ll be starting my new role with Omicia.  They’re a small company in the Bay Area, but they have a disproportionate passion for their work and some pretty cool ideas and connections. (Shoutout to the Yandell lab.  Yes, I’d like a few VAAST stickers, but I’m hoping to meet @zevkronenberg in person to ask for them one day…)

For the moment, I’m still in Vancouver, where I’ll stay until we find a place to live in the Oakland Area, but things are officially in motion.

Ironically, it’s been a long road to get here, since I first met up with Omicia about 3 years ago.  Somehow, it just took a long time for the stars to align… but here we are, and the real journey is about to begin.

Frontiers in Science Latex missing packages.

I’m working on a manuscript to be sent in to a frontiers journal, and discovered a few missing dependencies for LaTeX, so I figured I’d share them here.

If you find you’re missing chngpage.sty, install texlive-latex-extra

if you find you’re missing lineno.sty, install texlive-humanities

On a Mac, that’s:

sudo port -v install texlive-humanities texlive-latex-extra

Happy compiling.

What’s the point of doing a PhD? (reply to Kathy Weston)

I wanted to comment on a blog post called “What’s the point of doing a PhD” on Blue Skies and Bench Space, by Kathy Weston.  Right off the top, I want to admit that I’ve not followed the blog in the past, and my comments aren’t to say that Kathy doesn’t have a point, but that what she’s proposing is only a partial solution – or rather, it feels to me like it’s only half the picture.

Warning, I’ve not edited this yet – it’s probably pretty edgy.

I believe Kathy is responding to a report (Alberts et al) that proposes such things as cutting the numbers of postdocs, creating more staff scientist positions and making sure that non-academic PhD options are seen as successful careers.  Those are the usual talking points of academics on this subject, so I don’t see much new there.  Personally, I suspect that the systemic failures of the research community are small part of a far broader culture war in which research is seen as an “optional” part of the economy rather than a driver, which results in endless budget cuts, leading to our current system, rather than as an issue on it’s own.  However, that’s another post for another time.

Originally, I’d written out a point-by-point rebuttal of the whole thing, but I realized I can sum it up in one nice little package:  Please read all of Kathy’s criteria for who should get a PhD.  Maybe read it twice, then think about what she’s selecting for… could it possibly be academics?

Advice to undergrads could be summarized as: prepare for a career of 80 hour workweeks (aka, the academic lifestyle) and if you don’t know for sure why you’re getting your PhD (aka, to become an academic), don’t do it!   Frankly,  there are lots of reasons to get a PhD that don’t involve becoming an academic.  There’s nothing wrong with that path, but a PhD leads to many MANY 9-5 jobs, if that’s what you want, or sales jobs, or research jobs, or entrepreneurial jobs.  Heck, my entire life story could be summed up as “I don’t know why I need to know that, but it’s cool, so I’ll go learn it!”, which is probably why I was so upset with Kathy’s article in the first place.

Lets summarize the advice to PhD students: If you don’t know why you need to learn a specific skill, don’t do a post doc! I’m going to gloss over the rest of that section – I really don’t think I need a committee of external adjudicators to tell me if they think my dreams are firmly grounded, and if your dream isn’t to be an academic, why should you walk away from a postdoc?

Advice to postdocs: “This is your last chance to become an academic, so think hard about it!”  Meh – Academics R Us.  (Repeat ad nauseum for N-plex postdoc positions.)

Everything else is just a rehash of the tenure track, with some insults thrown in:  “Don’t hire mediocre people” is just the salt in the wound.  No one wants to hire mediocre people, but people who are brilliant at one thing are often horribly bad at another.  Maybe the job is a bad fit.  Maybe the environment is a bad fit.  Is there a ruler by which we can judge another person’s mediocrity?  Perhaps Kathy’s post is mediocre, in my opinion, but there are likely thousands of people who think it’s great – should I tell others not to hire Kathy?  NO!

I think this whole discussion needs to be re-framed into something more constructive.  We can’t keep the mediocre people of out science – and we shouldn’t even try.  We shouldn’t tell people they can’t get a PhD, or discourage them.  What we should be doing is three-fold:

First, we should take a long hard look at the academic system and ask ourselves why we allow Investigators to exploit young students in the name of research.  Budget cuts aren’t going to come to a sudden halt, and exploitation is only going to get worse as long as we continue to have a reward-based system that requires more papers with less money.  It can’t be done indefinitely.

Second, we should start giving students the tools to ask the right questions from early on in their careers.  I’d highlight organizations like UBC’s Student Biotechology Network, which exist with this goal as their main function.  Educate students to be aware of the fact that >90% of the jobs that will exist, once they’re done their degrees, will be non-academic.  A dose of accurate statistics never hurts your odds in preparing for the future.

Finally, we can also stop this whole non-sense that academia is the goal of the academic process!  Seriously, people.  Not everyone wants to be a prof, so we should stop up-selling it.  Tenure is not a golden apple, or the pot at the end of the rainbow.  It’s a career, and we don’t all need to idolize it.  Just like we’re not all going to be CEOs (and wouldn’t all want to be), we’re not all going to be professors emeritus!

If you’re an Investigator, and you want to do your students a favour, help organize events where they get to see the other (fantastic!) career options out there.  Help make the contacts that will help them find jobs.  Help your students ask the right questions… and then ask them yourself, why did you hire 8 post-docs?  Is it because they are cheap trained labour, or are you actually invested in their careers too?

Lets not kid ourselves – part of it is the system.  The other part of it is people who are exploiting the system.