Add the following to your gemfile:
ran bundle install from the application directory
//= require scribl
Enjoy using scribl-rails and creating cute bio-graphics! Many thanks to Chase Miller for the awesome library!
For more information and development check out the scribl-rails at github
Biogems.info is a new site for keeping track of new and existing Bioruby plugins. Plugins are separate code libraries that split functionality out of the Bioruby main tree. The idea is to have a core Bioruby release and to allow Ruby developers to contribute to Bioruby through plugins. According to Bonnal, the maintainer of biogem (the bio-plugin crafting tool), plugins are separately maintained and may represent experimental or work in progress.
To read more about Bioruby plugin system please refer to the wiki page on plugins.
The Bioruby development team has continued to work tirelessly to bring us the latest release of the Ruby bioinformatics library commonly referred to as bioruby. A list of all the new changes is available here . One of the most pleasant news for beginners is that the Bioruby tutorial has been updated thanks to Michael O’Keefe and Pjotr Prins. The Release is largely a bug fix release with updates on web services from SOAP to REST interfaces. Upgrading to the latest release is easy…
gem update bio
gem install bio
Like most informatics throughput methods, epitope prediction generates a lot of output and in a not so friendly format suitable for subsequent analysis. I considered writing a parser for the output using Ruby, but would that not take long? A simple vim function that I added to my .vimrc file to format the output and use a single keystroke worked the magic and saved time.
" formating output from netMHCII-pan program function! FormatNetmhcOutput() g/^\#/norm dd g/^--/norm dd g/^Protein/norm dd %le g/^pos/norm dd %s/<=\sWB//g %s/<=\sSB//g %s/\s\+$// %s/\s\+/,/g g/^$/d endfunction nmap ;h :call FormatNetmhcOutput()
This function can be called by pressing the ; and h key when in normal mode. It removes comments and provides a csv output that can be read with a simple R directive.
data <– read.csv("file.csv")