Statistical Computing with Pathway Tools using RCyc Tomer Altman - PowerPoint PPT Presentation

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Statistical Computing with Pathway Tools using RCyc Statistical Computing with Pathway Tools using RCyc Tomer Altman taltman1@stanford.edu Biomedical Informatics, Stanford University Statistical Computing with Pathway Tools using RCyc R &

Statistical Computing with Pathway Tools using RCyc Statistical Computing with Pathway Tools using RCyc Tomer Altman taltman1@stanford.edu Biomedical Informatics, Stanford University
Statistical Computing with Pathway Tools using RCyc R & BioConductor S: software community over 30 years of statistical computing, data mining, machine learning, and data visualization knowledge R: open-source S with a lazy Scheme interpreter at its heart (including closures, symbols, and even macros!) RCyc: an R package to allow the interaction between Pathway / Genome Databases and the wealth of biostatistics software in the R community
Statistical Computing with Pathway Tools using RCyc BioConductor Figure: BioConductor: Thousands of peer-reviewed biostatistics packages.
Statistical Computing with Pathway Tools using RCyc Software‘R’-chitecture C code extension to R to allow Unix socket access Common Lisp code to hack in XML-based communication Make the life of *Cyc API developers easier. Currently supports exchange of numbers, strings, and lists R code and documentation Provides utilities for starting PTools and marshaling data types Assumes user is familiar with the PTools API: http://bioinformatics.ai.sri.com/ptools/api/ All wrapped up in R package Easily installs via standard command-line R interface
Statistical Computing with Pathway Tools using RCyc Simple Example callPToolsFn("so",list("’meta")) callPToolsFn("get-slot-value",list("’proton", "’common-name")) callPToolsFn("get-class-all-instances",list("’|Reactions|"))
Statistical Computing with Pathway Tools using RCyc Availability http://github.com/taltman/RCyc Linked from PTools website
Statistical Computing with Pathway Tools using RCyc Next Steps Dynamic instantiation of API functions in R Coming next release (coordination with BRG) Make development of *Cyc APIs easier, less boilerplate code Frame to Object import/export Provide “RCelot” functionality to slurp Ocelot frames directly into R S4 reference objects for direct data access Support for more exotic data types Symbols, hash tables, arrays, structures, etc. Submission of package to BioConductor repository Rigorous vetting process
Statistical Computing with Pathway Tools using RCyc End Questions?

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