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Eamon O'Dea edited this page Sep 25, 2018 · 68 revisions

Page Editor: @e3bo
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Welcome to the Drake Lab Wiki!

A guide to editing the wiki is here and additional details are given in these pages.

This wiki is currently under heavy construction. The goal is to develop a handy guide, especially for newcomers, to the software tools and computational tactics that are useful for accomplishing work in the Drake lab.

I've copied top-level headings from the outline in the google doc, which include names of assigned writers. Assigned writers should feel free to start filling in subsections with subheadings and paragraphs, possibly as new wiki pages.

If you don't find the answer to the question you have, please submit an issue here.

The Drake Lab Philosophy to Doing Science

This section is currently a stub.

High Performance Computing Essentials - Eamon

This section provides a brief introduction to high performance computing (HPC) resources and techniques typically used by lab members. This includes tips and tricks for transferring, running and manipulating your files on remote computers such as clusters. You may need high performance computing for running data-analysis code in parallel, performing simulations, or processing large, spatial data sets, among other things. But before getting wrapped up in the technical details of a computationally intensive project, it is often worth considering whether you may achieve your goals with a simpler algorithm which requires few, if any, computational resources. On the other hand, computational resources keep growing and becoming easier to use, so using them may be the best choice. The links below provide an assortment of quick-start guides for routine HPC-related tasks in this lab.

Come here to learn how to install and get started using software for tasks commonly done in the Drake Lab.

Software

Project management - Paige

Come here when beginning a new project for steps to set up folder directory structure, ease electronic collaboration, and setting up version control, a system for managing projects over time.

Project Management

Data Management & Manipulation - Paige

Come here to learn about how to manage data from different sources, including how and where to store data in the Drake lab. This also includes information on making data manipulation reproducible through the use of scripts, especially in R.

Data Management

Coding Conventions

This covers our lab's approach to syntax and code review. (maybe a list of packages and contact people for each)

Data Visualization Practices - Michelle and Eric

Come here for general guidelines for designing figures, from layout to the R code to file formats.

Data Visualization Practices

Writing the manuscript - Robbie and Michelle

Come here to learn about the tools commonly used in the lab to write manuscripts and other documents. There are also several links to lab specific info on writing content.

Writing the manuscript

Links to other lab websites

Lab Links

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