Some time ago, I published a post called “A guide for the lonely bioinformatician” – this turned out to be one of my most popular posts, and has over 10,000 views to date.  Whilst I wrote that post to try and help those that find themselves as lone bioinformaticians in wet labs, that wasn’t initially my main motivation; at first, my main motivation had been panic – panic at the amount of bad science that lone bioinformaticians, without support, might produce.

Let me be clear, this isn’t the fault of the lone bioinformaticians themselves – any young scientist working in isolation will make mistakes – it is the fault of the PIs and heads of labs who employ said lone bioinformaticians with no cogent plan on how to support them.

You may get a sense of my motivation from the post itself:

I’ve seen more than one project where the results were almost 100% crap because a bioinformatician acted in isolation and didn’t ask for help

Then yesterday I had this conversation on Twitter:

Bioinformatics Unicorns

To summarise, we started with a clinical lab saying, quite rightly, that it is hard to recruit bioinformaticians; there were then many comments about how labs often want to employ people with rare and in-demand skills (so called “bioinformatics unicorns”) on poor salaries or boring projects, and that’s why it is difficult to recruit.

I agree with this, but that’s not the point I want to make here.

Many of you will be ahead of me at this point, but let me spell it out.  Lone bioinformaticians will make mistakes, often elementary mistakes, because they don’t have peer support or access to an expert in bioinformatics who can help them.  This matters less in research labs investigating e.g. the evolution of sea squirts, but clinical labs deal with data that can actually affect a patient’s health and/or treatment.

I am aware of a few lone bioinformaticians working in clinical labs.  I want to make this clear – this is a bad idea.  In fact, it’s a terrible idea.  Through no fault of their own, these guys will make mistakes.  Those mistakes may have dire consequences if the data are then used to inform a treatment plan or diagnosis.

So what’s the solution?  I can think of two:

  1. Pay more and employ more senior bioinformaticians who know what they’re doing, and build a team around those experienced bioinformaticians
  2. Collaborate with a bioinformatics group experienced in human genomics/genetics

To any lone bioinformaticians working in clinical labs, I would say this: find support; find help; make sure the things you are doing are the right things; have your pipelines reviewed by an independent external expert.  Don’t be alone.   This isn’t a personal attack on you – every young scientist makes mistakes, I certainly did – you need support and it’s important you get it.

To the clinical labs: I understand there are funding issues.  This isn’t a personal attack on you either.  But employing a lone (and inexperienced) bioinformatcian will almost certainly result in mistakes being made that would have been avoided by someone more experienced.  Please consider the options 1 and 2 above.