Bioinformatician Blunders

Researchers in the field share tips on how not to succeed in bioinformatics.

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I read the article and I

I read the article and I agree with most of what is being said, but many of the issues around code reuse and documentation are a problem of time. There are too few bioinformatician hired, the key word is hired, at most institutions. This means that most bioinformaticians are seriously over committed and are looking for easy (cheap) ways to complete work before they are yelled at by the PI. PIs do not understand software development AT ALL and if you do not have someone who can stand up and explain it, then these issues will continue. I can't tell you how many times I have heard "What do you mean that you need 4 weeks to properly analyze that data? I have the paper going out in 2 weeks" or "How can it take 6 months to develop a pipeline? I could get a grad student to do it in 2 weeks." The other refrain I hear is "It costs that much? I could add 1000 samples to my experiment for that amount of money." Sorry but you should have talked to me before writing the grant. Bioinformaticians and biologists share in the problems here.

Decades ago, Erwin Chargaff

Decades ago, Erwin Chargaff derided the developing field of molecular biology as "the practicing of biochemistry without a license." I wonder what he would have said about the state of our work today.

It is sad probably all the

It is sad probably all the words from your quote-endquote parts are true.

@sexton, It is sad probably

@sexton, It is sad probably all the words from your quote-endquote parts are true - PI's have much greater time pressure.

Considering that I spent ~

Considering that I spent ~ seven years at the bench before becoming immersed in bioinformatics, I agree with the concerns. My code is written with the biologist in mind. I tell my graduate students to always consider what will work for the biologist as well as commenting their code.

As "software is eating the

As "software is eating the world", Bioinformatics is going to drive life science research, mostly. Just look at your iPhone or Facebook. While hardware makers are thinking about a 3-5% margin as a "good year", software-driven companies such as Apple are either making or raising tons of cash (Facebook), and making lots of friends (aka customers). There are truly unique and elegant experimental designs or insights from exceptional life scientists, which happen about once a decade. Other than that those PIs think Biology is just spend the same amount of money to generate "1000 samples for their experiments" instead of pipelines or analysis are just sounding their own alarm. Of course you could throw whatever amount of money on MiSeq for thousands of sequencing samples, but without bioinformatic interpretations and data management, at the end they are still ... data, and lots of them. Those PIs think Bioinformatics is easy and quick and fail to realize the importance of it are actually shifting themselves in to something like the "manufacturing" or "crafting" roles.