The processed data from a genomics experiment can usually be stored in three tidy data sets. The first tidy data set is information about the phenotypes or about the samples. So that's this data set up here. So that data set usually contains information about, say, who are the cases and who are the controls. Information about, say, the batches that the samples were collected in. Or any other technical or biological information that will be used in modeling the genomics information. The second data set is the genomics data. So the genomics data is usually stored in a large data set like this. It's usually tall and skinny. In other words, there are usually a relatively few number of samples compared to the very many number of features that have been collected. And here by features I mean genes whose gene expression we've measured or SNPs that we've measured and crossed with a large number of individuals or any other information that's genomic that's been collected. Finally, the data set, the features data set tells you a little bit about the features that we've collected. So, it tells you about which genes you've measured or which SNPs you've measured in the population, and maybe some information about what genome they came from or any other information you might want to know about those. Say, what biological pathways they belong to or anything else. So an important thing to know is that a first check you always want to do is make sure that there are the same number of rows in the phenotype data as there are columns in the genomics data. Because the phenotype data represents the same samples that appear in the genomics data. Second, you want to make sure that there are the same number of rows in the features data as there are rows in the genomics data, because the features data says something about each of the features in the genomics sample. If those dimensions don't match, you know that you've got some kind of problem with some of the annotation in one or the other. Now, there should always be sample indicators. So, these are sample names that appear in this data set that match the sample names that appear in the genomics data. Similarly, you should have gene or SNP, or whatever other genomic feature IDs here that should match the gene and SNP and feature IDs that appear here. These are, again, basic checks that you can do to make sure that the data set has been processed and given to you in a way that you can handle.
