This article provide a brief background about power and sample size analysis. Then, power and sample size analysis is computed for the Z test.
Milano R net, in collaboration with Quantide, organizes
"Advanced R" Course
November 15-16, 2012
This course is designed for those already using R and willing to gain a more in depth perspective of R working mechanism along with an overview of several advanced topics ranging from "S4 programming frame" to parallel computation.
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