MultiMarkdown
Since I started using github in a serious way back in January I've begun writing my documentation in the markdown format that displays so nicely on github. Markdown is essentially a parsing tool and a simple text syntax that allows the easy conversion of human 'readable text' to html. It's intuitive, it took less than 5 minutes to pick up, and saves me a ton of time not writing HTML. However, its ease of use is tempered, a bit, by a lack of features. Although it is easy to create headers, lists, and code bocks - simple HTML stuff - it doesn't include the option to create tables, formated mathematical formulas, citations and bibliographies. Since I'm a scientist who wants to produce documents with these sorts of features, this is annoying.
Luckily, the markdown syntax has recently been extended, in a project called MultiMarkdown, to include many of the aforementioned features. Multimarkdown essentially merges the markdown syntax with LaTeX which, if you haven't heard of it, is a rather inscrutable, but extremely powerful text formatting language. It's popular in the CS and physics disciplines. LaTeX produces beautiful documents, but it's easy to spend a week or more adjusting the formatting and reading the API trying to figure out some of the more complicated features. Multimarkdown looks like it will do much of the more basic LaTeX formatting, but without the headache.
40 Essential Tools and Resources to Visualize Data | FlowingData
This looks incredibly useful. I really need to sit down and learn Flash and Processing.
40 Essential Tools and Resources to Visualize Data | FlowingData.
Blue Collar Bioinformatics
Just wanted to recommend Blue Collar Bioinformatics a slick blog with lots of useful bioinformatics scripts. Everything is written in python and the full working source is typically available on GIT.
F$@%ing R: Adventures with Tcltk in OSX
I've got a bunch of RNA-seq reads I need to analyze and for the the most part I've been writing my own code to do the analysis. However, a recent paper in BioInformatics (Wang et al. 2009) describes a new R package for the identification of differentially expressed genes in RNA-seq datasets. R is a pretty straightforward language with a built-in installation system so I should just have to type two lines of code...
source("http://bioconductor.org/biocLite.R")
biocLite("DEGseq")
Not so quick. When I ran this code R tells me it can't find the DEGseq library. A bit more poking around on the internets and I discover that there's an alternate download site:
source("http://bioinfo.au.tsinghua.edu.cn/software/degseq/DEGseqInstall.R")
But after installing some dependancies it also spits out a bunch of errors. I compare the errors... Hmmm... Both installs appear to by dying on the tcl/tk install, but tcltk is a default R library. I can see it right there in "/Library/Frameworks/R.framework/Resources/library". Two hours later and after trying a bunch of crap I find this helpful website:
http://cran.r-project.org/bin/macosx/tools/
A quick and dirty install of the tcltk-8.5.5-x11.dmg and now "library(tcltk") works like a charm. No errors.
I install DEGseq with the following set of commands:
source("http://bioconductor.org/biocLite.R")
biocLite("DEGseq")
Now, a day an a half later I can see if it's useful. Woo.
Citations:
L Wang, Z Feng, X Wang, X Wang, X Zhang. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics (2009)
Textmate Nexus Bundle
I wrote a very simple textmate bundle for working with nexus files.
Version 1 Functionality: folds NEXUS blocks, highlighting bayes block mcmc line and typing command-B will automatically calculate burnin at 25%, more to come as I think of it.... probably contains bugs
Download nexus bundle version 1. (03/05/09)
New measures of genetic differentiation
Lou Jost has pretty neat paper out describing new measures genetic diversity that accurately account for allelic differences. I've written some PYTHON scripts to parse genepop files, measure allele frequencies, and generate [some of] these measures of diversity. Enjoy.
http://www.ngcrawford.com/django/jost/
Jost L. 2008. GST and its relatives do not measure differentiation. Molecular Ecology,17(18), 4015 - 4026
