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Tools, tips, & resources compiled by fellows of the MIT Biological Engineering Communication Lab

Getting started

Below is a list of resources compiled for BE Communication Lab fellows relevant to undergraduate, graduate students, and postdocs at MIT. Although there are some MIT-specific resources, this list is also relevant to any STEM student/researcher.

The MIT BE Communication Lab resources are also stored within this repository and are highlighted within the list below. If you have any questions, email us at [email protected].

This list compiles resources to transform data into a clear message through:

  • data analysis and visualization,
  • figure design,
  • writing and reference management,
  • design tools and resources,
  • professional resources.

It also includes resources for reproducibility and miscellaneous tools for biological engineering research (e.g. plasmid design, flow cytometry analysis, next-generation sequencing).

Legend

Symbol Meaning
🆓 no upfront cost
🔓 open source
💵 small cost
💰 large cost
📦 Computing Package
📚 Resource

Computing

Programming

Students typical use the follow resources to analyze and plot data for class and research purposes.

  • Python 🆓 🔓 – general applicability, open-source; commonly used with Anaconda, a package and environment manager

  • R 🆓 🔓 - popular for bioinformatics, genomics, statistics; typically used with RStudio 🆓 using packages from CRAN

    • RStudio introduction to R - a good place to start for complete beginners.
    • Swirl teaches R within RStudio. A great interactive resource for beginners.

  • MATLAB 💰 - commercial computing environment offered at MIT for affiliates. See Gnu Octave for an open source 🔓 alternative.

  • Other computing languages/platforms used include Julia and Go, but their user bases are much smaller.

Computing Clusters at MIT

Computing clusters are available at MIT and affiliate institutions for use by students and non-affiliates.

  • Athena – computing environment offering remote environments with pre-installed software and file storage

  • TIG - CSAIL group offering computing services

  • AWS, Google Cloud, Microsoft Azure - commercially available services simple to setup with researcher funds

  • C3DDB - Boston-wide resource for life science researchers

  • Koch Institute Bioinformatics & Computing Core - offers a variety of cloud computing resources

  • McGovern Institute Core - Linux-based cluster offering storage and CPU/GPU performance

  • Other institutes (e.g. Broad Institute) and groups offer internal computing resources, inquire directly to gain access

Data Visualization

Data Visualization Resources

Plotting Tools

Python Plotting

  • matplotlib – the most popular plotting framework
  • Pandas - table management
  • bokeh – interactive web-based visualization
  • seaborn – opinionated plotting framework for statistical visualizations
  • plotly – interactive web-based visualization
  • altair – straightforward visualization framework, biased towards statistical plotting
  • Rpy2 - use R code in jupyter notebook
  • BECL notes - BECL-produced resource for python related plotting and getting started.

R Plotting

This is an opinionated summary of key tools for plotting in R, focusing primarily on the tidyverse group of packages📦.

  • ggplot2📦🔓 – the most popular plotting framework based on the book, Grammar of Graphics
  • plotly📦🔓 – commercially supported interactive web-based visualization tools
  • Shiny📦🔓 – interactive charts and applications on the web, great for displaying public data and generating publication website
  • reticulate📦🔓 - interface with Python via R
  • ggplot2 Cheatsheet sheet📚 - quick overview of ggplot2 plotting functions and aesthetics
  • ggplot2 Tutorial📚 - Harvard tutorial on getting started with ggplot2
  • R Graph Gallery📚 - gallery of plots generated using R
  • R for Data Science📚 - a comprehensive resource to become proficient at using R for all data science needs, written by lead instructors at RStudio

Other Plotting tools

  • RAW – fast, easy graphs from Excel or CSV files
  • Graphpad Prism – stand-alone plotting program
  • Excel – the one and only
  • Datawrapper – fast, easy graphs from Excel or CSV files
  • Octave – Free version MATLAB
  • WebPlotDigitiazer

Reproducible Analysis

General Principles

R workflows

  • drake 📦 – toolkit to build reproducible workflows that scale
  • rapport
  • knitr - allows to convert markdown, R, and plots/tables to html or PDF files, similar to Jupyter for python
  • workflowr
  • here - makes it easy for users to set directories and paths
  • ROpenSci

Python workflows

Writing

LaTeX

Markdown

  • Pandoc - for switching between .doc/.tex/.md/etc file types
  • Microsoft Word

Citations and Reference Management

  • Zotero 🆓 🔓
  • Mendeley 🆓
  • EndNote 💵
  • Papers 💵
  • Readcube
  • Jabref

Figures

Drawing

Image Manipulation

  • Adobe Photoshop 💰
  • Affinity Designer 💵
  • GIMP 🆓 🔓 The GNU Image Manipulation Program
  • ImageJ/Fiji 🆓 🔓

Design Tools & Resources

Color

Fonts & Typography

Icons

Images

  • Unsplash - downloadable high-quality images

Poster Design

Poster Design Tools

  • Adobe Illustrator 💰
  • Inkscape
  • Microsoft Powerpoint 💩
  • Adobe InDesign 💰

Poster Templates

Poster Galleries

Scientific Software

Chemical Structures

Analytical Chemistry

Protein Structure Visualization

Plasmid Editors

Flow Cytometry

Microscopy Analysis

Unsorted Weblinks

Professional Resources

Miscellaneous & Unsorted

License

CC0

To the extent possible under law, MIT BECL has waived all copyright and related or neighboring rights to the compilation of this list, but not the resources included.