Some blog updates

Yes, I’ve had a few minutes of time that I dedicated to my blog last night.  I’ve made great progress on my thesis, so I didn’t mind spending a few minutes in the evening writing, coding or learning a bit more about wordpress.  Frankly, I think my blog needed a few cosmetic updates anyhow.

First, I’ve customized the menu above.  Turns out it’s not hard to do in word press.  Once that was done, I wrote a new about page, added a couple links and then realized that the links on the right were redundant, so they’re gone now.  Yay progress.

The font size for the main text has been shrunk.  If it’s too small for anyone, let me know.  I had always felt it was a bit too large, so I’m glad it wasn’t too hard to do.

I also added a link to my old blog, but then discovered that wordpress offers a half-assed method of importing from blogger.  Unfortunately, none of the comments made it over, but the nearly 400 blog entries from my old blog did (albeit with some funky extra “>” characters).  However, that makes my old blog pretty much obsolete, so if I ever get the comments to move over, I’ll take down the website and the new button as well. At any rate, you can use the search bar on the right to go through all of my blog posts from 2006 till now (minus the ones at Nature blogs, of course).

That means that my site now spans just over 5 years, covering some 555 posts (including this one) and 106 categories.   That’s an average of about 111 posts a year, or about 2 posts a week.  I’m sure my conference blogging skews that number, but it’s not insignificant.  Wow.  I certainly hadn’t thought I’d been blogging that much…!

Finally, I’ve also changed my blog’s perma-links from the ugly /?p=XXX format to one that reflects the date and title of the post.  The old format should also work if you’re linking here from an old URL, but it won’t be how I refer to posts from now on.  Just thought you should know.

So, no major changes, but a lot of little details.  I hope they make my blog a bit more usable and readable… and perhaps just a little more professional looking.  If there’s anything I’ve missed that would be useful, don’t hesitate to let me know.

Guilt

I went to a seminar on thesis writing last year.  They warned us that this would happen…

There’s only so much time in a day.

I feel guilty if I’m not working on my thesis.

I feel guilty if I’m neglecting my blog.

I feel guilty if I’m not working on other projects.

I feel guilty if I work instead of spending time with my family.

Given the finite amount of time available in a day, it’s a fine balancing act.  I just hope I don’t drop something…

A Reply to: Should a Rich Genome Variant File End the Storage of Raw Read Data?

Before you read my post, you might want to zip over to Complete Genomic’s blog where C.S.O. Dr. Rade Drmanac wrote an entry titled “Should a Rich Genome Variant File End the Storage of Raw Read Data?”  It’s an interesting perspective where he suggests that, as the article’s title might indicate, we should only be keeping a rich variant file as the only trace of a sequencing run.

I should mention that I’m really not going to distinguish between storing raw reads and storing aligned reads – you can go from one to the other by stripping out the alignment information, or by aligning to a reference template.  As far as I’m concerned, no information is lost when you align, unlike moving to a rich variant file (or any other non-rich variant file, for that matter.)

I can certainly see the attraction of deleting the raw or aligned data – much of the data we store is never used again, takes up space and could be regenerated at will from frozen samples of DNA, if needed.  As a scientist, I’ve very rarely have had to go back into the read-space files and look at the pre-variant calling data – and only a handfull of times in the past 2 years.  As such, it really doesn’t make much sense to store alignments, raw reads or other data. If I needed to go back to a data set, it would be (could be?) cheaper just to resequence the genome and regenerate the missing read data.

I’d like to bring out a real-world analogy, to summarize this argument. I had recently been considering a move, only to discover that storage in Vancouver is not cheap.  It’ll cost me $120-150/month for enough room to store some furniture and possessions I wouldn’t want to take with me.  If the total value of those possessions is only $5,ooo, storing them for more than 36 months means that (if I were to move) it would have been cheaper to sell it all and then buy a new set when I come back.

Where the analogy comes into play quite elegantly is if I have some interest in those particular items.  My wife, for instance, is quite attached to our dining room set.  If we were to sell it, we’d have to eventually replace it, and it might be impossible to find another one just like it at any price.  It might be cheaper to abandon the furniture than to store it in the long run, but if there’s something important in that data, the cost of storage isn’t the only thing that comes into play.

While I’m not suggesting that we should be emotionally attached to our raw data, there is merit in having a record that we can return to – if (and only if) there is a strong likelyhood that we will return to the data for verification purposes.  You can’t always recreate something of interest in a data set by resequencing.

That is a poor reason to keep the data around, most of the time.  We rarely find things of interest that couldn’t be recreated in a specific read set when we’re doing genome-wide analysis. Since most of the analysis we do uses only the variants and we frequently verify our findings with other means, the cost/value argument is probably strongly in favour of throwing away raw reads and only storing the variants.  Considering my recent project on storage of variants (all 3 billion of the I’ve collected), people have probably heard me make the same arguments before.

But lets not stop here. There is much more to this question than meets the eye. If we delve a little deeper into what Dr. Drmanac is really asking, we’ll find that this question isn’t quite as simple as it sounds.  Although the question stated basically boils down to “Can a rich genome variant file be stored instead of a raw read data file?”, the underlying question is really: “Are we capable of extracting all of the information from the raw reads and storing it for later use?”

Here, I actually would contend the answer is no, depending on the platform.  Let me give you examples of what data I feel we do a poor example of extracting, right now.

  • Structural variations:  My experience with structural variations is that no two SV callers give you the same information or make the same calls.  They are notoriously difficult to evaluate, so any information we are extracting is likely just the tip of the iceberg.  (Same goes for structural rearrangements in cancers, etc.)
  • Phasing information:  Most SNP callers aren’t giving phasing information, and some aren’t capable of it.  However, those details could be teased from the raw data files (depending on the platform).  We’re just not capturing it efficiently.
  • Exon/Gene expression:  This one is trivial, and I’ve had code that pulls this data from raw aligned read files since we started doing RNA-Seq.  Unfortunately, due to exon annotation issues, no one is doing this well yet, but it’s a huge amount of clear and concise information available that is obviously not captured in variant files.  (We do reasonably well with Copy Number Variations (CNVs), but again, those aren’t typically sored in rich variant files.)
  • Variant Quality information: we may have solved the base quality problems that plagued early data sets, but let me say that variant calling hasn’t exactly come up with a unified method of comparing SNV qualities between variant callers.  There’s really no substitute for comparing other than to re-run the data set with the same tools.
  • The variants themselves!  Have you ever compared the variants observed by two SNP callers run on the same data set? I’ll spoil the suspense for you: they never agree completely, and may in fact disagree on up to 25% of the variants called. (Personal observation – data not shown.)

Even dealing only with the last item, it should be obvious:  If we can’t have two snp callers produce the same set of variants, then no amount of richness in the variant file will replace the need to store the raw read data because we should always be double checking interesting findings with (at least) a second set of software.

For me, the answer is clear:  If you’re going to stop storing raw read files, you need to make sure that you’ve extracted all of the useful information – and that the information you’ve extracted is complete.  I just don’t think we’ve hit those milestones yet.

Of course, if you work in a shop where you only use one set of tools, then none of the above problems will be obvious to you and there really isn’t a point to storing the raw reads.  You’ll never return to them because you already have all the answers you want.  If, on the other hand, you get daily exposure to the uncertainty in your pipeline by comparing it to other pipelines, you might look at it with a different perspective.

So, my answer to the question “Are we ready to stop storing raw reads?” is easy:  That depends on what you think you need from a data set and if you think you’re already an expert at extracting it.  Personally, I think we’ve barely scratched the surface on what information we can get out of genomic and transcriptomic data, we just don’t know what it is we’re missing yet.

Completely off topic, but related in concept: I’m spending my morning looking for Scalable Vector Graphics (.svg) files for many jpg and png files I’d created along the course of my studies.  Unfortunately, jpg and png are lossy formats and don’t reproduce as nicely in the Portable Document Format (PDF) export process.  Having deleted some of those .svg files because I thought I had extracted all of the useful information from them in the export to png format, I’m now at the point where I might have to recreate them to properly export the files again in a lossless format for my thesis.  If I’d just have stored them (as the cost is negligible) I wouldn’t be in this bind….   meh.

 

10 Tips for how to get the most from your PhD.

I’m clearly late to this conversation, but because I disagree with the first two contributors, I figured I might as well have my say.

First, there was @Katie_PhD‘s post on “How to make the most of your PhD: The road less traveled“., which (alas) doesn’t give you much of a sense of how to get more out of your PhD.  It’s a great piece, so don’t get me wrong – I’ve read it several times already – but there aren’t any tips for graduate students.

Following on, Nick at “For Love of Sciences” wrote a list of tips that could help incoming and early PhD students get more out of their PhD.  Unfortunately, I’m not sure I really believe Nick’s points cover the topic the way I’d like to see it covered.  Some of them are dead on: Yes, you should move out to a new city, to find a new environment and challenge yourself, but other’s I find myself disagreeing with Nick.  Alas, that’s the point of graduate school, really – to stand up for what you believe in, and boldly state when you think other people aren’t nailing the point as accurately as possible.

So, without further ado, let me introduce my top 10 tips for how to get the most out of your grad school experience.

1. Say yes, until you learn to say no.

When you start graduate school, you won’t know enough about which avenues are the right ones to follow up.  Learn to say yes at first, to tackle any project that comes your way.  You’ll find yourself tackling good projects and bad projects and, as time goes by, you’ll learn how to tell which projects are the bad ones in order to start saying no to them.  When you’re ready to graduate, you’ll even have to turn down a few of the good ones in order to keep your PhD from dragging on too long.  So start with yes, but learn how (and when) to say no.

2. Learn to communicate.

Half of the challenge of a PhD program is to become a good communicator.  Define what good communication means to you and then bust your ass to figure out how you can become as good as possible at it.  Whether that’s communicating science to non-scientists, communicating with your peers, blogging, twittering or even writing grants, make a commitment to learn to communicate in every possible form and then to get better at it.  At the end of your PhD you are going to be judged by how well you can defend your ideas, so why not practice it as often as you can?

2b.  Learn to teach.

Teaching is just another form of communication, but it’s an important one that just can’t be overstated.  If you become an academic, you’ll be evaluated on how well you teach your students.  If you become a blogger, you’ll be evaluated on how well you can teach your audience.  If you become an entrepreneur, you’ll be evaluated on how well you can teach your board about your technology.  The job of a scientist is always teaching and communicating, so get as much practice (and hence feedback) as you can while you can.

3. Take advantage of your university’s resources.

Every university that I’ve had the pleasure of visiting has had some form of courses for it’s graduate students to learn new skills – TAKE THEM!  I’ve gone to some really cheese-tastic courses, and I’ve gone to some life-altering good ones.  You never know which one is which till you try them out, but if you don’t try any of them, you’re tossing away a perfectly good opportunity.

4.  Meet your future life partner.

I cheated on this one – I met my wife while we were doing our masters degrees together, but it was still graduate school and I had been planning on doing a PhD at the time.  Regardless, when else will you be surrounded by people who are fascinated by the same things you are, smarter than you are, and are fantastically interesting people in their own right?

4b.  Make some great friends.

Yeah, even if you don’t meet the love of your life, you can definitely find a few friends.  I’ll admit, I haven’t made a lot of close friends during my PhD, but I’ve made up for that with a wide net of professional contacts and having had the opportunity to rub shoulders with a lot of fantastically interesting and successful scientists.  I wouldn’t have traded it for anything.

5. Decide what you stand for, and stand for it.

Along the long and winding road of your PhD, you’ll discover situations that test your morals, your sense of dignity and your ideals.  Everyone is sorely tempted to sweep a bit of dirt under the figurative carpet of their project in the name of having results to show off.  If you don’t believe me, spend some time reading the retraction watch blog. What separates the good scientists from the bad scientists is the moral code to which they hold themselves.

I’ve taken stands on open source code, on re-doing experiments and on re-coding units that were just “good enough.”  Grad school gives you a great opportunity to do the things that matter to you – and do them well.  This is one of the few times that you get to show people who you really are and not compromise on it.

6. Keep good notes

Pretty much everything you do, you’ll either have to show someone else how to do it, or do it over again later.  The better your notes are, the easier things will go for you – and that includes when it comes time for you to write up your thesis.  Trust me, good notes and documentation will make your life SO much better when you’re writing a chapter and want to figure out exactly how that algorithm worked, or need to make last minute changes to a poster  at 3am and can’t remember how you churned out that table…

7.  Be a sponge.

Grad school is also one of the few times that you can really delve into projects that you wouldn’t otherwise have a chance to pursue in a corporate environment.  I’ve learned such random/wonderful things as how to play ping pong, how to use professional publishing software and how to draw cartoons.  You never know when these things will come in handy.   (For the record, there are far better examples, but those were way more amusing to me.)

8. Face the challenges.

Not many graduate students get slapped down for trying to take on more responsibility or to tackle the tougher projects.  I’m constantly amazed by the people who just quietly slide through grad school without leaving a ripple behind:  Life doesn’t start once you’re finished – it’s already going on, so hiding behind your desk isn’t going to help you get anywhere.

Perhaps I’d sum it up this way: Have the courage to face problems head on, tackle projects that are bigger than you are and throw yourself into the fray.  The worst thing that’s likely to happen is a bruised ego, but even that’s sometimes a lesson worth learning – and it’s a lesson that’s much easier to learn as a student than in the corporate world.

9.  Don’t give up.

People will ridicule you, people will flame you in emails, projects will misfire, scholarship applications will be rejected.  These are facts of life.  You can’t make everyone happy all the time and even keeping yourself happy can be a challenge some days.  Remember that there is always a light at the end of the tunnel and if you persevere, you will get through.

An investor once told me a brilliant piece of advice in relationship to startup companies, which I’ll paraphrase and apply to grad school.

“Grad school is like a roller coaster: some days will be crazy high, some days will be desperately low.  Sure, you can enjoy the highs, and you’ll despair in the lows, but don’t let either of them change your course – keep a straight and level path and you’ll get through to the end of the ride. “

And that brings me to the last point…

10.  Enjoy the ride.

The longer you spend as a grad student, the more impatient you’ll be to leave, but that doesn’t mean you can’t enjoy the time you spend there.  You’ll rarely have such a wonderful combination of responsibility  (or lack thereof), freedom (or at least, lax deadlines) and community (how ever you want to define it.) –  Remember to appreciate what you have while you have it, because things will change once you hand in your thesis.

Here’s to that day coming as soon as possible!  Cheers!

External examiner required

It’s one of those long standing traditions of academia – having your work examined by someone who has no stake in your future career.  In theory, this should liberate the external examiner from feeling obliged to grant unworthy applicants a degree, but in practice, I have the sinking suspicion that, to the examiner, it probably just feels like one of those thankless tasks that really doesn’t have any reward.

Although I can’t actually do anything to make it more rewarding for whomever steps up to the plate for my thesis, other than try to make my writing as easy to read as possible, I thought I might start by casting the net a bit wider than the average grad student’s search – in the hopes of finding someone with a real interest in reading my thesis.

If this were a job application it would go something like:

Wanted: One External Examiner.  Must be an academic with interest in at least two of:

  • Chip-Seq Algorithms
  • Large databases
  • Human cancer variation
  • Breast cancer

Applicant will be required to read and comment on a 120+ page document, and either appear at an as yet unscheduled thesis defense, or to send comments via email.  Successful applicants will be allowed to twitter or blog the defense, if desired.. Compensation will not be commiserate with experience… or with anything else, for that matter.

Does that appeal to anyone?

In any case, I fully expect to start putting together a list of names in the next couple weeks.  I should mention I’m not really expecting anyone to step forward, but I would be thrilled if someone did.

Other Thesis Related Matters: The document currently sits at 92 pages of text/figures/refs, with what feels like about 65-70% of the content I want to put in.  I anticipate having a reasonable first draft in about 3 weeks, putting my thesis defense roughly in November-December.  I’m still debating doing all of edits in an open manner on the web, but I will not be opening up any of it until after my committee has seen at least one draft, at the earliest.

BlueSeq Knowledgebase

Remember BlueSeq?  The company I gave a hard time after their presentation at Copenhagenomics?  Turns out they have some cool stuff up on the web.  Here’s a comparison of sequencing technologies that they’ve posted.  Looks like they’ve put together quite a decent set of resources.  I haven’t finished exploring it yet, but it looks quite useful.

Via CLC bio blog – Post: Goldmine of unbiased expert knowledge on next generation sequencing.

Nature Comment : The case for locus-specific databases

There’s an interesting comment available in Nature today (EDIT: it came out last month, though I only found it today.) Unfortunately, it’s by subscription only, but let me save you the hassle of downloading it, if you don’t already have a subscription.  It’s not what I thought it was.

The entire piece fails to make the case for locus-specific databases, but instead conflates locus-specific with “high-resolution”, and then proceeds to tell us why we need high resolution data.  The argument can roughly be summarized as:

  • Omim and databases like it are great, but don’t list all known variations
  • Next-gen sequencing gives us the ability to see genome in high resolution
  • You can only get high-resolution data by managing data in a locus-specific manner
  • Therefore, we should support locus-specific databases

Unfortunately, point number three is actually wrong.  It’s just that our public databases haven’t yet transitioned to the high resolution format.  (ie, we have an internal database that stores data in a genome-wide manner at high resolution…  the data is, alas, not public.)

Thus, on that premise, I don’t think we should be supporting locus specific databases specifically –  indeed, I would say that the support they need is to become amalgamated in to a single genome-wide database at high resolution.

You wouldn’t expect major gains in understanding of car mechanics if you, by analogy, insisted that all parts should be studied independently at high resolution.  Sure you might improve your understanding of each part, and how it works alone, but the real gains come from understanding the whole system.  You might not actually need certain parts, and sometimes you need to understand how two parts work together.  It’s only by studying the whole system that you begin to see the big picture.

IMHO, Locus-specific databases are blinders that we adopt in the name of needing higher resolution, which is more of a comment on the current state of biology.  In fact, the argument can really be made that we don’t need locus-specific databases, we need better bioinformatics!

How I would improve Google plus, or “Squares, not Circles”

First off, I absolutely think Google+ is fantastic and I’m thinking of giving up twitter in favour of it, which should say a lot.  I think it has the ability to be THAT good.  However, google missed something big.  As “Science of the Invisible” points out (and via tech crunch) – Google circles are great for organizing, but don’t really help you in the noise to signal ratio.

So, I’d like to propose a new Idea:  Google Squares.

Instead of the loosely grouped people that make up circles, a Square would be a rigidly defined group, with moderators.  The moderators have two roles: determining who can post to a Square, and who can follow a Square.

Imagine, if you will, a private Square. Lets imagine I want to start a Square for my family.  I can first decide to make it private – only people who are invited to the square are allowed to see the posts, and only those in my family are invited.  It becomes, instantly, the equivalent of an email mailing list (but much easier to set up and manage) for my family members.  I don’t have to worry about typing in the email address of my family every time I want to post something to the Square – and neither do my other family members.  Only one person needs to set it up (the moderator), and it instantly becomes a useful communication tool for everyone I add.

It would be useful for labs, social groups, clubs, etc.   And, it moves people away from email – a long time holy grail of security experts.

So, what about public Squares? They could be even more useful – providing the equivalent of a blogging consortium, or twittering group (which don’t even really exist.)  Imagine if there were a Square with all of your favorite twitter-ers. You can still follow them all, one by one, if you like, or add them to your circles, but the square would give you instant access to All those people who someone else has pre-screened as being good communicators and worth following.  Instant increase in signal-to-noise.

Finally, the last piece lacking is direct URLs.  Seriously, I’m a bit miffed that google didn’t set this up from the start, even based on the google ID.  Really, I’ve had the google id apfejes for a LONG time – why can’t I have plus.google.com/apfejes.  Even twitter has this one figured out.

In any case, these are minor grievances…. but I’m waiting for Google to up their game once more.  In the meantime:

Do not disturb my circles! – Archimedes

Google+ goes to battle…

After playing with Google+ for part of a day, I have a few comments to make.  Some are in relation to bioinformatics, others are just general comments.

My first comment is probably the least useful:  Google, why the hell did you make me wait 3 days to get into Google+, only to then let EVERYONE into it 3 hours later after activating my invite?  Seriously, you could have told me that I was wasting my time when I was chasing one down.

Ok, that’s out of my system now. So on to the more interesting things.  First, this isn’t Google’s first shot into the social media field.  We all remember “The Wave”.  It was Google’s “Microsoft Moment”, that is to say, their time to release something that was more hype than real product.  Fortunately, Google stepped back from the brink and started over – so with that in mind, I think Google deserves a lot of credit for not pulling a Microsoft. (In my dictionary pulling a Microsoft is blowing a lot of money on a bunch of adds for products that really suck, but will get critical mass by sheer advertising.  eg.  Bling. Cloud. Need I say more?)

Ok, what did google get right?  Well, first, it seems that they’ve been reading the diaspora mailing list, or at least paying attention.  The whole environment looks exactly like Diaspora to me.  It’s clean, it’s simple, and unlike facebook, is built around communities that don’t have to overlap!  With facebook, everyone belongs to a single group, while Diaspora brought the concept of groups, so that you can segment your circles.  Clicking and dragging people into those groups was what convinced me that Diaspora would be a Facebook killer.

Instead, Google+ has leapfrogged and beaten Diaspora.  And rightly so – Diaspora had it’s faults, but this isn’t the right place for me to get into that.  As far as I can tell, everything I wanted from Diaspora has found it’s way into Google+ with one exception: You can’t host your own data.  Although, really, if there’s one company out there that has done a good job of managing user data (albeit it has stumbled a few times) it’s Google.  The “Do no evil” moto has taken a few beatings, but it’s still a good start.

[By the way, Diaspora fans, the code was open source, so if you’re upset that Google replicated the look and feel, you have to remember that that is the purpose of open source: to foster good development ideas. ]

So, where does this leave things?

First, I think Google has a winner here.  The big question is, unlike the wave, can it get critical mass?  I think the answer to that is a profound yes.  A lot of the trend setters are moving here from facebook, which means others will follow.  More importantly, however, I think getting security right from the start will be one of the big draws for Google.  They don’t need to convince your grandmother to switch to facebook – they just need you to switch, and your grandmother will eventually be dragged along because she’ll want to see your pictures. (And yes, Picasa is about to be deluged with new accounts.)

More importantly, All those kids who want to post naked pictures of themselves dancing on cars during riots are going to move over pretty damn quickly.  Whether that’s a good thing or not, I think EVERYONE learned something from the Vancouver Riots aftermath.

So great, but how will this be useful to the rest of us?  Actually, I’ve heard that Google+ is going to be the twitter killer – and I can see that, but I don’t see that as the main purpose.  Frankly, the real value is in the harmonization of services.  Google has, hands down been one of the best Software as a Service (SAS or SAAS) provider around in my humble opinion.  When your Google+ account talks to your email, documents, images – and lets you have intuitive fine grained control over who sees what, I think people will find it to be dramatically more useful than any of the competition.  Twitter will either have to find a way to integrate into Google+ or to figure out how to implement communities of their own. It may be a subtle change, but it’s a sea change in how people interact on the web.

For those of you who are bioinformaticians, you won’t be able to take Google+ lightly either.  Already, I’ve found some of my favorite scientist twitterers on Google+ and some have started posting things.  Once people start getting the hang of the groups, it won’t be long till we’ll see people following industry groups, science networks and celebrities.  (Hell, even PZ Myers has an account already.)

The more I think about it, the more I see its potential as a good collaboration tool, as well.  Let me give an example.  If group management can be made into something like a mailing list (ie, opt-in with a moderator) , a PI could create a “My Lab” group that he only allows his own students and group members to join, it would be a great way to communicate group announcements.  It doesn’t spill out information people who aren’t interested, and other people can’t get into those communications unless someone intentionally “re-tweets” the content.  Merge this with Google calendar, and you have an instant scheduling system as well.

What does Google get out of this?  Well, think targetted google adds.  As long as you’re logged in, Google will know everything about you that you’ve ever thought about.  And is that a bad thing?  Well, only if you’re Microsoft and want to complain about Google’s absolute monopoly of the online advertisement market.  You know what Microsoft?  Better them than you.  (And hey, if Google adds do help me find a good canoe when I’m in the market for one, who’s going to complain?)

Extinguish the HST? A summary of silliness.

For those of you who don’t have the pleasure of living in British Columbia, Canada’s most western province, I thought I’d share with you our current (and slightly stale) obsession: the Harmonized Sales Tax.

To briefly recap, BC elected the BC liberal party (as opposed to it’s only viable alternative, the BC New Democratic Party) back into power in 2009.  Both the liberals and the NDP have terrible histories of scandals, abuse of power and other skulduggery, most of which just makes BC citizens somewhat cynical about the whole political system. However, during the election, absolutely nothing was said about changing the (at the time) current tax system – a 7% provincial sales tax on top of a 5% federal goods and services tax, which many people think should have been a major debate for the election campaign.  (Opinions differ as to whether it had even been considered at the time.)

Lo and behold, one of the first things the re-elected liberal government did was sign an agreement with the Federal government (which was busy trying to re-brand itself as the Harper government, despite the fact that our political system doesn’t work that way, and that it’s illegal to boot) in order to merge the provincial and federal taxes (the PST and the GST) into the harmonized sales tax (HST).

In reality, it’s not a bad thing, since both levels of government were collecting nearly identical taxes in parallel.   If that’s all that had been in the agreement, it might have been a reasonable argument, but to muddy the water and spark off conspiracy theories, the Federal government bundled in a big payment to the province to bail it out from some other debts, incurred by recession induced budget shortfalls.

Unfortunately, at this point, a former premier (the equivalent to a state governor) decided he’d been out of the limelight for too long and decided to make a name for himself crusading against the tax.  (He’s a former NDP, of course, and the liberals were the ones who modified the tax system so it was only natural that this would be a great crusade for him to try to bring down the liberals.)  Indeed, he created enough of a protest that the elected premier resigned and the Liberals had to elect a new premier. (We don’t directly elect the head of our governments at any level in canada.)  The NDP, crushed by their loss, despite the unpopularity of the premier in some circles, also elected a new leader, just to wipe the slate clean for both parties.

The incoming premier, and our now current premier, was in power when a report came out saying that the tax exemptions don’t quite match up between the previous PST + GST and the HST.  That is to say, the government actually was taxing people more by harmonizing the two taxes and using the federal list of what is taxable and what isn’t.  This was more fuel for the fire, as people started getting quite upset over a number of items that were previously exempt at the provincial level.  Thus, previously, people were paying 5% tax on things before and suddenly found themselves paying 12% tax on the same items under the HST.

Despite the propaganda, the list of items for which the tax actually increased isn’t that onerous – and does have measures to protect the poor, although some people continue to claim that the poor are the ones paying the most tax.

So, between the ex-premier running around making statements that the HST is undemocratic and doing some serious rabble-rousing, and people being upset that they’ll pay more (anywhere between $350-1200 per year, depending on who’s actually telling the truth), the current government felt enough pressure to agree to reduce the HST to 10% from 12% AND to hold a referendum on the tax itself.

So, here I sit, with a referendum ballot on my desk, choosing between the Anti-HST side [Warning, following that link will expose you irrational arguments], claiming that a tax is undemocratic, and the pro-HST side that now thinks it’ll be able to operate with the equivalent of a ~20% cut to revenue. Neither one is looking too smart going into this battle.

Furthermore, the referendum, being conducted by mail, comes with the following instructions:

  1. Mark an X or Checkmark in ONE of the two circles next to the question
  2. Remove the ballot allong the dotted line
  3. Put the ballot in the Secrecy Envelope (A), close and seal the envelope
  4. Put the Secrecy Envelope (A) in the Certification Envelope (B), close and seal the envelope
  5. Complete the [form on the] Certification Envelope (B) […]
  6. Put the Certification Envelope (B) in the yellow ballot package envelope (C), seal the envelope
  7. Put the yellow ballot package envelope in the mail […]

The ratio of envelope to ballot is obscene (BC probably lost a forest for this ballot) and, in case you didn’t notice, step 6 forgets to tell you to close the envelope before you seal it. Oops.

So, in the end, I’ve cast my vote and checked off the No to “extinguishing the HST“, and see if the government can operate with a 10% HST, instead of going back to a system in which taxes are collected twice on the same items.  We might all be poor in the future, but we will at least be a little more efficient.

British Columbia, you may be the best place on earth ™ but this whole affair is insane.