This two days course shows wide variety of “Advanced R” topics ranging from S4 methods and classes to parallel computing in order to provide an exhaustive overview of R capabilities.
Second Milano R net meeting took place on September, 27.
More than thirty R users joining both the presentations session and the open bar.
- Welcome presentation
Andrea Spanò, Partner at Quantide
(download PDF, 3.0 MB)
- Introduction to the next Italian BioR event at PTP
Andrea Pedretti, Parco Tecnologico Padano
(download PDF, 0.2 MB)
- Applications of technical risk assessment in Food Industry by R
Carlo Leardi, Tetra Pak Packaging Solutions S.p.A.
(download PDF, 1.1 MB)
- R and Bioconductor for the analysis of massive genomic data
Niccolò Bassani, University of Milan
(download PDF, 4.4 MB)
A very interesting paradigm in data analysis comes from the necessity to model data where it is difficult to think of a single global function to be capable to represent adequately the data.
We could see a spectrum of models going from the global statistical model, with a single function and associated probability distribution, to the decision tree fitting a set of constants at each leaf of the tree.
September 27, 2012 - 18:00 - 21:00
Fiori Oscuri Bistrot & Bar (www.fiorioscuri.it)
Via Fiori Oscuri, 3 - Milano (Zona Brera)
In the previous post we saw how much convenient could be GenABEL in the management of genotypic/phenotypic data.
We introduced the import of genotypic data from an Illumina format file:
> convert.snp.illumina(inf = "gen.illu", out = "gen.raw", strand = "file")
but what happens if you're analysing your data with PLINK, the open source toolset for GWAS?
This article gives a brief overview of the data.table package written by M. Dowle, T. Short, S. Lianoglou.
A data.table is an extension of a data.frame created to reduce the working time of the user in two ways:
- programming time
- compute time