We just did a ton of next-gen on … and we were hoping that you could help analyze the data,” I feign a smile and resist the urge to crawl under my desk. Consequently, when a graduate student or colleague knocks on my office door and says, “Hey, Dave. But I am a far cry from being able to perform, for example, the in-depth analyses needed for high-quality metagenomics work. Of course, I have picked up some computational skills along the way, enough to assemble and analyze the mitochondrial and chloroplast genomes that encompass my research life.
Like many evolutionary biologists, my research relies heavily on molecular sequence data, and because of this I am sometimes categorized as a bioinformatician-admittedly, I occasionally market myself as one-when, in fact, I am merely an end user of sophisticated software, pipelines, and programs that genuine bioinformaticians have designed. Sadly, I may have disappointed some of my colleagues.
I had been working as an assistant professor of biology for over 6 months when I finally figured out what kind of scientist the department was actually hoping to get: a bioinformatics fix-it-all, a quick cure for their expanding genomic woes, an in-house computational genius willing to lend his powers to every graduate thesis containing a next-generation sequencing (NGS) dataset. Sometimes, it is not until after you have started a new job that you get a sense of the skills your employer was looking for when hiring you.
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