51–60 of 179 posts
Really makes me want to learn more about molecular biology. Any solid factual resources besides the references mentioned in this justified rant?
"A Hitchhikers Guide to Next Generation Sequencing"
Part1: http://blog.goldenhelix.com/?p=423
Earlier quoted context omitted.
>There can be a big opportunity cost in trying to rework a workflow so that it is more efficient and then test it thoroughly ensure correctness. Hi, I recognize your name as a legit bioinformatician, am a huge fan of the lab that you're currently in, and others should listen to you. I'd like to add that for many projects, general reusable software engineering is not necessarily a huge advantage. Instead of verifying…
> and if it's a good idea, it will be worth polishing the turd later, Which of the released turds do you consider to be polished?
In terms of next-generation sequence analysis, Heng Li's BWA mapper and Samtools libraries are fairly good. His coding style is a bit terse for my tastes, but it keeps out people who don't know what they're doing, it's very clear code for semi-complicated algorithms, and BWA is some of the most reliable software I use everyday.
On the infrastructure side, Galaxy [https://main.g2.bx.psu.edu] is getting fairly good.
The BioConductor repository of R packages is extremely mixed. I don't like some of their architectural choices, but it's ended up working out OK.
I still use Michael Eisen's Cluster from a decade ago, along with Java TreeView.
When someone finds fault with the way a field conducts itself, I would implore them to constructively influence that field. You might be surprised how many are actually sympathetic to your concerns.
I'm not dismissing this author's concerns: to do that would really require knowing the molecular biology field (which is more than sequencing, it turns out). I do neuroscience right now, and programming can be a problem for some. But a constructive suggestion to change can have much more impact than a long rant.
[0] http://www.runmycode.org/data/MetaSite/upload/nature10836.pd...
Earlier quoted context omitted.
Hi, I'm a bioinformatics researcher. Apparently I work for this guy's ex(?)-employer although I have never heard of him before. My single most limited resource is programmer time. My time and the time of other people who work with me. I have access to loads of computers that sit idle all the time, even if it is on nights and weekends. There is zero opportunity cost to me in using these computers more fully. I have en…
Well, I can call myself a bioinformatics researcher, I guess, as I have CS Ph.D working in genetics/genomics. I see your point of throwing computers at simple solutions as cheaper than throwing good programmers. I do that too. We are very fortunate in that we write run-once programs that only have to work in one environment using one inputs. However, bad programmers write incorrect programs, which give wrong conclusi…
If you work with that mentality, you're asking for trouble. Well, not so much asking for trouble, but sending Trouble a voicemail that says "We're over here, you lazy bastard, just see if you can mess something up!"
Earlier quoted context omitted.
The Duke situation to which you refer was fraud, not just a result of programmer error or poor engineering practice.
It was initially a programming error but the Duke researchers refused to acknowledge it and reanalyze their data, because that might mean retracting their prominent paper. From there it just snowballed. It was certainly fraud after the error was pointed out to them. There might also be other elements of fraud in their paper. I watched a presentation by MD. Anderson researchers who spotted the error and spent more tha…
Earlier quoted context omitted.
Well, I can call myself a bioinformatics researcher, I guess, as I have CS Ph.D working in genetics/genomics. I see your point of throwing computers at simple solutions as cheaper than throwing good programmers. I do that too. We are very fortunate in that we write run-once programs that only have to work in one environment using one inputs. However, bad programmers write incorrect programs, which give wrong conclusi…
>I have seen people parsing Gigabytes-files with one line of Awk I feel exactly the opposite. I'm suspicious of anyone that does not use AWK (or other Unix text utilities) as a standard tool for checking the integrity of multi-gigabyte files, or generating summaries. AWK is super-fast, allows highly flexible checks, and allows quick and reliable interaction with huge amounts of data in the way that a script can not.
Earlier quoted context omitted.
> and if it's a good idea, it will be worth polishing the turd later, Which of the released turds do you consider to be polished?
Pretty much anything that gets used by many people ends up getting polished (the exception being the RNA-seq field, it's still pretty rough out there, but the research is still taking quite a while). And if you're writing software, your tool isn't going to get used until it's somewhat polished, or is so unique and essential in its purpose that people have to use it. In terms of next-generation sequence analysis, Heng…
"Look at the disgusting state of the samtools code base. Many more cycles are being used because people write garbage. For a tool that is intimately tied to research, the absence of associated code commentary and meaningful commit messages is very poor. The code itself is not well self documenting either."
commit log:
http://samtools.svn.sourceforge.net/viewvc/samtools/trunk/sa...
code:
http://samtools.svn.sourceforge.net/viewvc/samtools/trunk/sa...
John Graham-Cumming (jgrahamc here) co-authored a piece on making scientific code open. It was received well-enough that Nature published it [0]. This approach has inspired others to do better work by describing a concrete problem, then outlining steps to fix it on an individual and institutional level. When someone finds fault with the way a field conducts itself, I would implore them to constructively influence tha…
It's a similar issue. I think statisticians are taking constructive steps to correct their path, since you know, ML is the new sexy thing. Bioinformatics could take a much longer time to self-correct though.
Although, as I mentioned in an earlier comment, Fred seems to be in a prime position to disrupt the bioinformatics field since he seems to know all the problems that afflict it