Popular Tweets
A list of popular tweets by retweets and favorites.
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This is your periodic reminder of free #rstats learning content that we’ve produced largely in response to the DataCamp incident. I want my students to feel valued and safe. First off: The R-Bootcamp. No install required, just browser: r-bootcamp.netlify.app/
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Want to learn the basics of #Shiny? Our gRadual intRo to Shiny workshop is now online (videos, Rstudio.cloud project, and slides). #rstats #DataVisualization laderast.github.io/gradual_shiny/
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Repost because I can't spell: Yes, I am crazy. I'm teaching another online course this term, an introduction to #rstats and the #tidyverse called Ready for R. I'm happy to share materials/RStudio Cloud notebooks if external folks want to take a stab at it. ready4r.netlify.com
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Have you always wanted to learn the #rstats #tidyverse with a gentle approach, and online? Our R-Bootcamp requires only a web-browser (it works on phones as well!) r-bootcamp.netlify.com/
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Advice I always seem to give to students in their presentations. 1. If you have multiple figures on a slide, animate them, and introduce them 1 at a time. 2. Be really careful with tables. Highlight important information. Don't expect everyone to just "get it".
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If there is one lesson I can teach future analysts: If you want someone to draw a conclusion from a figure, state that conclusion. Don't expect that person to "just get it" from that figure. In fact, make that conclusion the title of your figure.
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.@datapointier and I have updated our #rstats R-Bootcamp, which focuses on tidyverse, to use @_inesmontani's free and open course format: r-bootcamp.netlify.com/
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I was not expecting @hadleywickham to start #rstudioglobal with self-soothing, one of the foundations of cognitive behavioral therapy.
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#ready4r news: new version is now available to everyone. Come learn #rstats and the #tidyverse for free and with friendly videos and Rstudio.cloud notebooks. No installation required! Sign up here: ready4r.netlify.app/mailing
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Do you have a group that wants to learn how to make more effective figures using #rstats and ggplot2? Take a look at my Data Storytelling Workshop, with slides and lesson notes. github.com/laderast/data_storytelling_bdc It also runs on @mybinderteam, no R installs needed: mybinder.org/v2/gh/laderast/data_storytelling_bdc/master?urlpath=rstudio
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#DataCamp Instructors - I made a package to convert your #rstats course repos to the awesome open course format made by @_inesmontani. I'd love help testing it with your courses, since I only have my repo. github.com/laderast/decampr
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I know that bash scripting is the missing link for a lot of bioinformaticians. My book "Bash for Bioinformatics" (in draft form) aims to give you essential bash skills that are useful in running cloud compute jobs. laderast.github.io/bash_for_bioinformatics/
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I know that @DataCamp is offering a free trial right now. But don't forget how they tried to cover up a sexual harassment scandal of their then-CEO. I haven't seen any real improvement on their side. buzzfeednews.com/article/daveyalba/datacamp-sexual-harassment-metoo-tech-startup @StatStas/1262067535387615233
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Good morning. Just a reminder of some of my free #rstats courses: R-Bootcamp: interactive #tidyverse tutorials: r-bootcamp.netlify.app/ Ready for R (videos/rstudio projects): ready4r.netlify.app/mailing/ {tidyowl} (intermediate tidyverse topics): github.com/laderast/tidyowl
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I think bioinformaticians need to have a really strong shell scripting background. We underemphasize the importance of this (in terms of time spent learning) compared to R/Python. This is especially important when running cloud jobs and you need to glue together code.
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Hi Everyone. I'm teaching an #rstats course next quarter. One assignment is to have each student write about a #tidyverse function. What it's for and an example. What are some less known #tidyverse functions that do a job you find useful?
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One lesson I think is the hardest for students to learn. There usually isn't a "correct" answer in an analysis, only more defensible ones. And you need to be flexible, and not dogmatic, in how you do your analyses.
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I've been slowly going through "JavaScript for R". Its treatment of how to build an htmlwidget and set up JS dependencies is one of the best I've ever seen. Kudos, John Coene! #RStats #JS #shiny book.javascript-for-r.com/
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Hi Everyone. I've decided to leave OHSU and academia. This has been a really hard decision to make. I've accepted a position as a bioinformatics trainer for DNANexus. I have many reasons, which I've outlined here: laderast.github.io/posts/2021-04-29-moving-on-and-upwards/
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Constantly reminded of how much of bioinformatics is transforming one file format into another file format.
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My meager accomplishments this year: 1. Left academia. 2. Felt pretty good about it. 3. Realized my own worth.