sleq

A sleek package to deal with sequences in R. Joint O'Meara lab project, created in a hackathon.

To install it:

library(devtools)
install_github(bomeara/sleq)

March 2016 Hackathon

Oct 2015 Hackathon

Results

• One undergrad, five grad students, three postdocs, and a faculty member came up with issues over the course of a couple of lab meetings
• Before the hackathon, we created an example function and a new class for sequence alignments
• At the hackathon, we split into pairs and chose issues to work on
• We mostly kept to our goals of using unit testing and roxygen throughout. The main exception was some pre-existing code in this area from people's own work that was simply incorporated, with unit testing to be added later.
• Ten lab members committed code to this project; for many, it was the first time using version control software, issue tracking, and the like.

The code now has:

• seqalignment class: can be subset with brackets like a character matrix, but internally has slots for info on codon position, gene name, and data type. Tested.
• Code to subset these objects in various ways.
• Code to merge these objects, even with partial taxon overlap: combine COI and 18S alignments, for example.
• Code to filter for areas of bad alignment.
• Code to automatically find the reading frame that will minimize stop codons. Tested.
• As well as other code that is less well tested, but still in development.

Archived info from the day of the hackathon

This will be developed at an inhouse hackathon on Oct. 12, 2015. A secondary objective is to make useful code, but the primary objectives are learning and lab bonding. To that end:

• We will be using roxygen2 for documentation
• We are doing unit testing with testthat -- intro here. In our case, we will write tests for a function, which it will fail at first, then we will write code to make it work.
• We will be doing pair programming: this results in better code, but more importantly helps the primary objectives of learning and bonding (unless the pairs fight, in which case it becomes learning that you're not bonding).
• We'll be using Google's R style guide.
• We are using a shared github repo (here!). Note that if you submit new code by doing pull requests, you can get a free, geeky t-shirt
• Lab members: before we start, get a github account. I advise using a permanent email address (UT will kick you out after you leave).

Some notable features of the sleq package:

• Sequences are stored as character matrices, thus easy to subset.
• However, we also have a seqalignment class. It can be indexed using [] as with a character matrix, but actually stores this internally. The object also has info about gene locations and sequence type.