This article provide a brief background about power and sample size analysis. Then, power and sample size analysis is computed for the Z test.
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.
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