There are some crazy powerful tools out there for proteomics in R.
Wait! Don't leave!
If you completely dismissed this 'cause you've heard this before from some dumb bioinformatics wannabe down your hallway and it was all junk -- or you tried it yourself and found it impossible --
Check this out!
Point 1: Yes, the bioinformatics field is having lots and lots of problems with fakers. How could they not? There are jobs open everywhere for them -- and unscrupulous people -- or uninformed interviewers are going to make an increasing number of mistakes. So you're going to find some people who can hardly handle Excel who have somehow scored a 6 figure salary and the title "bioinformatician." Similar things have been known to happen in our field from time to time....
Point 2: Just follow the link and scroll down though this paper! This is so clearly described -- and the important scripts and their functions so well highlighted that I seriously thing that I could do this! Why do I feel like I recently had an anti-command line rampage recently...?
I guess the point of this post is -- don't get frustrated yet cause the first 4 "bioinformaticians" you interacted with got their jobs cause they looked the part (it is very cool right now for kids to look like they get beat up a lot -- even the dumb ones) and don't mistrust the field. There are some seriously good people out there -- producing very good software -- that works!!
Or...can you come up with another way to get dual PCA plots of your differential data that autoscales?
Thank you Ben, for these encouragements.
ReplyDeleteAnd if you never need any help with any of my software, I am always happy to help.
I think you make a really good point about uninformed interviewers. But it goes beyond that: writing innovative big data/*omics grants without a good grasp of data analysis; writing relevant job adverts for bioinformaticians; once hired, providing support for the lonely pet-bioinformatician [1]; ... Serious biology departments ought to have at least one computational faculty.
ReplyDeleteThis quote from [2] hits the nail on the head.
Informatics is underfunded, yet most times is the true differentiator between genomics groups; differentiation is key for academic survival!
And it's valid for proteomics, any field dealing with high throughput data.
[1] http://www.opiniomics.org/a-guide-for-the-lonely-bioinformatician/
[2] http://massgenomics.org/2016/12/this-year-in-genomics-and-next-gen-sequencing.html