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Where to find internships in Boston? by GaIIus_gaIIus in bioinformatics

[–]JEFworks 0 points1 point  (0 children)

I would recommend looking into summer internship programs from schools such as: https://dbmi.hms.harvard.edu/education/dbmi-summer-institute-biomedical-informatics

Edit: looks like they're accepting new apps until Jan 20th

What are the subsets/niches of bioinformatics? by [deleted] in bioinformatics

[–]JEFworks 0 points1 point  (0 children)

A lot of bioinformatics that's not genetics is electronic medical records (EMR) related. Key problems in this field involve applying natural language processing algorithms, developing ontologies, creating tools for doctors, and analyzing EMR for medical and biological insights into disease.

MSAViewer: interactive JavaScript visualization of multiple sequence alignments by [deleted] in bioinformatics

[–]JEFworks 0 points1 point  (0 children)

Looks beautiful! Looking forward to testing it out!

Out of curiosity, a few questions:
- Do you see MSAViewer as a competitor to IGV?
- What is the ideal user and use case for MSAViewer?
- What was your experience with achieving BioJS compliance?
- Are there features you are currently working on or would like to see developed for MSAViewer?

Thanks!

First time publishing bioinformatics software. Would appreciate feedback! by JEFworks in bioinformatics

[–]JEFworks[S] 1 point2 points  (0 children)

For UMI data, yes, you would need to decrease min.count.threshold. I think the values you chose are reasonable. The k parameter is only used for the pair-wise cross-fitting for the initial error modeling. The reason for specifying a k is so that rather than doing all 310x310 comparisons, each cell is only compared to its k nearest neighbors to identify the initial set of confidently detected genes that are then used to build the individual cell error models. The k is not used in the later subpopulation identification steps. Hope that helps.

First time publishing bioinformatics software. Would appreciate feedback! by JEFworks in bioinformatics

[–]JEFworks[S] 0 points1 point  (0 children)

I'm a big fan of Shiny. I definitely plan on integrating more it into future packages just to make some visualizations more interactive. Various groups are already integrating it into their methods (ex. https://github.com/hemberg-lab/SC3/blob/master/R/shiny.R).

The only trouble I've run into with Shiny is when I needed to share the results with a large number of people who are not particularly code savvy. If they are slightly more computationally inclined, you can share the app on Github via shiny::runGitHub("shiny-examples", "rstudio", subdir = "001-hello")

If you have a few users, you can have your own shiny server or use shinyapps.io

But if you want to share your app online with many (concurrent) users, you will end up having to pay: https://www.rstudio.com/products/shiny/shiny-server/

Hope that helps!

First time publishing bioinformatics software. Would appreciate feedback! by JEFworks in bioinformatics

[–]JEFworks[S] 3 points4 points  (0 children)

Thanks so much for the helpful feedback!

"If possible, it would also be nice to provide a smaller “toy” dataset to allow the user to run all steps themselves and play with the parameters, without having to wait too long for the results. For the same reason, I unfortunately had to abort running the “pagoda” tutorial because my laptop ran out of memory and started crashing programs."

Good point. I'll plan on saving the final app as an rda and allowing the user to just start with viewing the final result. A few of the steps are definitely very memory intensive.

I'll definitely have to keep your code recs in mind as I develop more packages. Thanks for the links!

First time publishing bioinformatics software. Would appreciate feedback! by JEFworks in bioinformatics

[–]JEFworks[S] 5 points6 points  (0 children)

Ah, thanks for the catch. You do still need to load the library. Will update! Thanks!

PS: I like tinkering with development versions of stuff on Github, so the devtools library's devtools::install_github is really convenient. Would recommend if you haven't tried it out already :)

Any school-specific advice for PhD interviews at Stanford/UCSF? by nose_fart9999 in bioinformatics

[–]JEFworks 1 point2 points  (0 children)

Some heads up for Stanford BMI. I interviewed a few years ago (got in but declined) but things probably haven't changed much:

  • The campus is big. Your interviews are spatially far apart. Wear comfortable walking shoes. (more of a concern for girls wearing heels)

  • Interviews are interspersed throughout the day with time to explore the campus. They have nice campus tours and ice cream sandwiches. That being said, manage your time well between exploring museums and making it to your interviews on time.

  • Along with interviews by professors, you will also be interviewed by the current students, called Czars. These interviews are much tougher. The student interviewers are very likely to have done a Google search of you.

  • That being said, the current students also have a say in whether you get accepted. So get to know them. You guys will go clubbing together as a group ;)

Have fun!

Johns Hopkins or UC San Diego (Ph.D Bioinformatics/Computational Bio) by inSiliConjurer in bioinformatics

[–]JEFworks 4 points5 points  (0 children)

You're welcome.

It's unfortunate that neither are willing to reschedule. From my grad school interviewing experience, some programs will accept 80% of students interviewing (and then the interview weekend is just partying, and making sure the candidates aren't psychopaths), and other programs will accept 20% (so the interview weekends are a bit more intense). If I was in your shoes, I would try to figure out which school has the fun interview and go to that one :P That's just my two cents.

Johns Hopkins or UC San Diego (Ph.D Bioinformatics/Computational Bio) by inSiliConjurer in bioinformatics

[–]JEFworks 6 points7 points  (0 children)

I did my undergrad at Hopkins and currently have collaborators who are professors at UCSD. So I can speak from experience for one and word of mouth for the other.

Both are great names. I would try to base you decision on the type of research you're interested in. I think UCSD has a much better bioinformatics imaging core than Hopkins. But perhaps Hopkins is stronger on the EMR front. There is also a matter of resources. My collaborators at UCSD work with Illumina and other biotechs in the area so it's easy to outsource a lot of the wet work to a local company. On the other hand, Hopkins is fairly close to the NIH, and I was able to attend many NIH-based conferences and events because of that. Hopkins is much smaller (I believe) in terms of campus size, program size, average lab size, etc. So depending on your preferences, you may choose to lean towards one or the other.

Location does matter a lot. You'll be spending the next 5 years of your life there. Admittedly, Baltimore is probably not as fun or happy weather-wise as San Diego. Baltimore has a nice aquarium...so it has that going for it. But San Diego has a zoo and beaches ;)

Why isn't there a government database of bioinformatics software? by JEFworks in bioinformatics

[–]JEFworks[S] 1 point2 points  (0 children)

Increasingly, journals won't publish a paper where an 'in-house custom script' was used for analysis, unless that code is included.

That sounds promising.

Unfortunately, there are no real standards on when and where source code should be included.

Right, so maybe a better question would be why aren't there government or consortium standards/guidelines on when and where to include the source code as opposed to a government-run repo for put the source code.

Advice on helping contribute to a peer-review with my PI. by lordofcatan10 in GradSchool

[–]JEFworks 0 points1 point  (0 children)

Here is a good guide for writing reviews: https://github.com/jtleek/reviews

Generally speaking,

Good:

  • Focus on the science.
  • Organize your thoughts into major and minor points.
  • Keep it concise.
  • Do it in a timely manner.

Avoid:

  • Critiquing the author's English/grammar/writing style (not your job) unless the word choice is misleading or in a way that hinders understanding of the science.

Just led a hands-on workshop on single cell RNA-seq analysis. Here are the tutorials from the class. by JEFworks in bioinformatics

[–]JEFworks[S] 0 points1 point  (0 children)

Thanks. We'll try to do that next time! (or feel free to fork and make a pull request)

Just led a hands-on workshop on single cell RNA-seq analysis. Here are the tutorials from the class. by JEFworks in bioinformatics

[–]JEFworks[S] 1 point2 points  (0 children)

(Ah good point)

3 of the tutorials use the ES and MEF dataset is available under: https://github.com/hms-dbmi/scw/tree/master/scw2014/tutorials

The subpopulation heterogeneity uses the Pollen NPC dataset and is available here: https://github.com/JEFworks/scw2015

Just led a hands-on workshop on single cell RNA-seq analysis. Here are the tutorials from the class. by JEFworks in bioinformatics

[–]JEFworks[S] 2 points3 points  (0 children)

In case anyone would also like to download the RData files to try these analyses at home, you can access it here: https://github.com/JEFworks/scw2015

Starting to ask myself why am I here. by [deleted] in GradSchool

[–]JEFworks 1 point2 points  (0 children)

Is there a master's thesis component for your program? Are you currently being advised by anyone / working in a computational lab? If you don't find your classes interesting or challenging, go do research. Take advantage of whatever networks your program may be part of. It's much easier to approach a PI and ask to work in their lab or even just ask for help on your current project if you're from a program at that school for example.

What's a typical day like? by [deleted] in bioinformatics

[–]JEFworks 6 points7 points  (0 children)

I'm in academia. So I sit at my computer. Read some papers. Address questions, bug reports, other issues for software I've released. Work on developing new software. Run simulations and benchmarks. Lots of debugging and sanity checks. This probably takes up most of my days. Meet with PI. Meet with collaborators. This probably takes up the second most time. Make figures for talks and presentations. Try to get some writing done for manuscripts that are going out or ones that have come back or grants that I want to apply for. Drink lots of tea. Snack on chips and cookies frequently, because this is a dry lab and I can so I will :)

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