Reproducible research

• Best Practices for Scientific Computing (paper)
• Ten simple rules for reproducible computational research (paper)
• Top ten reasons not to share your code
• Computational and Policy Tools for Reproducible Research (slides for a talk by Roger Peng)
• Roger Peng’s 2009 ENAR course: Methods for Reproducible Research
• Reproducible Research in Signal Processing - What, why, and how
• Replication, reproduction, and remixing in research software
• Implementing reproducible research (book; chapter PDFs online)
• Starting data analysis and wrangling with R, Stian Håklev

Make

• GNU make
• Manual for make
• Minimal Make tutorial
• Managing projects with GNU make book (part of the Open Books project)
• Software carpentry’s make tutorial
• Mike Bostock’s “Why Use Make”
• GNU Make for reproducible data analysis by Zachary Jones
• Makefiles for R/LaTeX projects by Rob Hyndman

Unix command line

• Survival guide for Unix newbies
• Settling into Unix
• Shell programming with bash
• Essential Unix commands
• Basic Unix commands
• Command line essentials (slides)
• How to look like a unix guru
• Linux essentials
• Important unix commands
• UW-Madison software carpentry tutorial on the shell
• A command-line murder mystery
• Command-line bootcamp
• Book: Learning the bash shell
• Karl’s .bash_profile and .bashrc files
• How to install the Xcode command line tools (Mac)
• Git for Windows for Git BASH and other command-line tools in Windows
• Mintty and ConEmu are terminal emulators for Windows.

R

• Art of R programming (book, pdf)
• Advanced R
• Testing R Code

RStudio, emacs, vim

• RStudio
• RStudio documentation
• Navigating code in RStudio
• Emacs Wiki
• Book: Learning GNU Emacs, 3rd ed
• Karl’s .emacs file
• Viper mode to mimic vi key bindings in emacs [Manual | Installation]
• Evil: Vim features within emacs
• Vim
• Vim Tips wiki
• Vim-R-plugin [github], like ESS for Vim
• Book: Learning the vi and Vim editors

Knitr, Markdown, Asciidoc

• knitr
• knitr in a knutshell
• Dynamic Documents with R and knitr (book)
• R Markdown
• Markdown
• MathJax
• knitrBootstrap for nice-looking reports (see L. Collado-Torres’s post)
• pander, an R package that is especially good for making tables with knitr, R Markdown, and pandoc.
• xtable. an R package for creating LaTeX and HTML tables; it’s better for LaTeX than for HTML.
• asciidoc
• knitr resources
• polymode, an emacs mode that handles R Markdown nicely

Git, Github and Bitbucket

• Karl’s git/github guide
• GitHub
• Education discount on GitHub personal account (allows private repositories)
• Happy Git and GitHub for the useR (from Jenny Bryan’s Data Science course
• Pro Git book
• The git documentation
• The github help pages
• Software carpentry notes on git
• Git can facilitate greater reproducibility and increased transparency in science (paper)
• Karthik Ram’s slides
• git - the simple guide
• magit, an emacs mode for git
• Tutorial on magit; also this one

Organizing projects and data

• Hadley Wickham’s paper on Tidy Data
• KnitR’s stitch() and spin()
• Nine simple ways to make it easier to (re)use your data (paper)
• Some simple guidelines for effective data management (paper)
• Quick guide to organizing computational biology projects (paper)

Writing clear code

• Best Practices for Scientific Computing (paper)
• Tidyverse style guide
• Oliveira & Stewart, Writing scientific software (book)
• Kernighan & Plauger, The elements of programming style, 2nd ed (book)
• Kernighan & Pike, The practice of programming (book)

R packages

• Hadley Wickham’s R Packages book
• Documenting R packages and functions, from that book
• Karl’s R package primer
• devtools package
• Jeff Leek on developing R packages
• Hilary Parker on making a simple R package
• Stat 545 guide to writing an R package
• Writing R extensions (official manual): [pdf | html]
• Developing R packages with RStudio
• How to build package vignettes with knitr
• Rd2roxygen package: Translate Rd files to roxygen comments
• Building R packages on Windows
• Karl’s largely out-of-date page about building R packages on Windows
• A web service for building and checking R packages for Windows: upload page
• R for Mac developer’s page
• R for Mac tools

Testing and debugging

• assertthat and testthat packages
• Hadley Wickham’s paper on testthat
• Testing in the R Packages book
• Debugging in Hadley Wickham’s Advanced R book
• Dr. Climate blog post on testing your code
• Yihui Xie’s testit package
• Jeff Leek’s notes on developing R packages talk a bit about unit tests
• Software Carpentry on testing
• Marick, The craft of software testing (book)
• Agans, Debugging (book)
• Debugging with RStudio

Big jobs

• KnitR cache [Also see Knitr options]
• KnitR chunk references
• Parallel R (book)
• A no BS guide to the basics of parallelization in R at librestats <!–
• Parallel Options for R slides by Glenn Lockwood –>
• HTCondor
• UW-Madison Center for High Throughput Computing
• Kill Linux processes easier with pkill
• Reproducibility of parallel tasks in R

LaTeX

• LyX, a WYSIWYG application for LaTeX, with knitr
• Overleaf, Authorea: online collaborative LaTeX editors
• Setting up LaTeX by Rob Hyndman
• A not so short introduction to LaTeX
• Getting started with LaTeX (pdf)
• Slides with introduction to LaTeX
• A hitchhiker’s guide to LaTeX (pdf)
• Detexify² - LaTeX symbol classifier
• xtable, an R package for creating LaTeX and HTML tables
• xtableGallery (pdf vignette)
• UnicodeIt (for Mac) - convert latex expressions into unicode characters
• LaTeXit (for Mac) - LaTeX-based equation editor
• LaTeX table generator
• AucTex, for working with LaTeX within emacs.

Slides and posters

• LaTeX Beamer
• Beamer Quickstart
• Beamer appearance cheat sheet
• LaTeX templates for conference posters
• Modern, simple presentations written in R Markdown by Benomics
• How to give a scientific presentation (pdf) [source on github]
• PDFjam
• LaTeX poster templates
• Nathaniel Johnston’s poster template

Python

• Python for biologists
• Software Carpentry
• Python Scientific lecture notes
• Jupyter notebooks
• Practical computing for biologists (book)
• Bioinformatics programming using Python (book)
• Python scripting for computational science (book)
• Python unittest introduction
• Python nose unit testing quick start
• Differences between Python 2 and 3
• What’s new in Python 3.0 (vs 2.6)
• Guide to getting started with Data Science and Python by Thomas Wiecki
• Learn Python for epidemiology (particularly regarding pandas)

Copyright and software/data licenses

• Victoria Stodden:
  • What computational scientists need to know about Intellectual property law (pdf)
  • The legal framework for reproducible scientific research (pdf)
• Coding horror blog
• Understanding open source and free software licensing (book)
• The whys and hows of licensing scientific code by Jake VanderPlas
• A quick guide to software licensing for the scientist-programmer (Morin et al. PLoS Comput Biol 8:e1002598, 2012)
• Creative Commons licenses
• tl;dr legal: Software licenses in plain English
• MIT license at wikipedia
• GNU General Public License
• GPL frequently asked questions
• Copyright basics (pdf from US Copyright Office)
• Works for hire (pdf from US Copyright Office)
• Fair use (US Copyright Office)
• Copyright basics
• Copyright and fair use
• Copyright of facts and data [concise]
• Database legal protections [detailed]
• VertNet guide to copyright and licenses for dataset publication
• UW-Madison:
  • Intellectual property rights
  • Intellectual property policies and procedures (pdf)
  • Copyrightable instructional materials

Human subjects research

• HIPAA
• Human Research Protection Program at UW-Madison
• De-identification of HIPAA data