The rasterList package has been created to make complex operation on spatially gridded region. Here's how to use it when analysing raster data.
Can you track your health status and your BMI simply by entering some personal data? Let's see how we did it with a brand new Shiny app.
It's very convenient manage data with R: you can import your dataset, you could find many packages which respond to your needs, then you could plot your results.
However it could be very bothersome retrieve the data from online databases. You need to use the specific API and maybe write your scripts using a new programming language, then you have to convert your data in a table format and finally import them with R.
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?