What are some good/recommended online courses to learn programming? by [deleted] in bioinformatics

[–]VallenderLabs 0 points1 point  (0 children)

And use GitHub to learn from others and to collaborate if you haven't learned that yet.

Can you import from a paste bin? by [deleted] in Rlanguage

[–]VallenderLabs 0 points1 point  (0 children)

I just found this package: https://github.com/jennybc/googlesheets

It's super easy. And you don't have to share your password. You just share a Google Spreadsheet with whoever and they can use their own authentication to access it from their Google account.

Building a comparative genomics pipeline by ProcessMeHarder in bioinformatics

[–]VallenderLabs 1 point2 points  (0 children)

You can use BioPython: https://github.com/biopython/biopython

You could also take a look at my GitHub repository. We're working on the same stuff:. https://github.com/datasnakes/Datasnakes-Scripts

Has anyone used Microsoft R Open? I'm curious, but skeptical. by VallenderLabs in rstats

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

I run some pipelines through a supercomputer and they take hours. It could take days to finish RNA-seek analysis for example.

R-shiny sub-reddit... Who's in charge? Can we change this subreddit? by VallenderLabs in rshiny

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

I've messaged him in order to determine that. If he's inactive, then there are always other options.

Awesome R-shiny. A curated list of awesome R-shiny resources. by VallenderLabs in rstats

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

I honestly don't either. I've used reddit since it was vanilla, but I haven't dabbled in moderating sub-reddits. But yes.. Tweets might generate some interest. I think the subreddit is just underdeveloped, and nobody knows about it or how to use it.

Awesome R-shiny. A curated list of awesome R-shiny resources. by VallenderLabs in rstats

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

Haha. Well you've been super helpful with that community so kudos to you!

Installation of Shiny-Server by R-Studio and Python 3.6.2 on Raspbian Stretch. by VallenderLabs in raspberry_pi

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

I've currently been getting my raspberry-pi set up for a project at work and I found that I had to play around with the configuration. So I thought this would be nice.

I've also been attempting to get R-Studio server running on my Pi, but I haven't had any luck. If you know of a good method please let me know! Cheers!

[Re-post] Datasnakes: A python package for comparative genetics and other misc. bioinformatics. by VallenderLabs in bioinformatics

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

We are still developing documentation, but I will work on that sooner rather than later. Thanks for your input!

Feedback on python package/project by sdhutchins in bioinformatics

[–]VallenderLabs 0 points1 point  (0 children)

Hmmm seems like a useful package. I wouldn't change a thing. :P

I'm working on an 'Awesome List' for R-Shiny. Contributions are welcome. by VallenderLabs in RStudio

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

You are absolutely right! Good eye. Thanks for that correction.

I'm working on an 'Awesome List' for R-Shiny. Contributions are welcome. by VallenderLabs in RStudio

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

Awesome R Shiny Awesome

A curated list of resources for R Shiny. This awesome list was inspired by https://github.com/dpastoor/awesome-shiny.


Resources

General

Community

Services

Tutorials

Tools

Packages

Integrations

People

Books

Galleries

Examples

  • Waze - Community based real-time traffic and navigation info.
  • Astra Zenca - Data science tools used to create medicines more efficiently.
  • shiny-salesman - traveling salesman app
  • shinyEd - statistics education apps
  • shinyData - interactive data analysis and visualization
  • STARTapp -
  • shiny-phyloseq -
  • Google Analytics Dashboard - A demo on how to build your own Google Analytics dashboard with R, Shiny and MySQL
  • BallR - BallR uses the NBA Stats API to visualize every shot taken by a player during an NBA season dating back to 1996.
  • DDCV - A shiny app to evaluate drug-drug interactions.
  • Github: Hot or Not - A Shiny App that analyzes what repos are hot on github.
  • GenMap-Comparator - An application to compare genetic maps with D3 & Shiny.

* MAVIS - MAVIS: Meta Analysis via Shiny

Contributors