Your links all describe DESeq, while that package is replaced by DESeq2 and therefore should no longer be used.
I am just getting started with R and I am looking for differentially expressed genes between men and women. The problem is, as I browseVignettes, I find I am just copying commands and arguments without really knowing what they mean. For example, which(phenoData(lgg_data)$idh1_mutation_found=="Yes" is given as an example. The string has so many things going on, and being new to programming I am having a hard time. Is there a DESeq resource that goes through these commands and arguments? I have an R book, but it doesn't go into "phenoData" and "mutation" and these biological areas.
2 answers
Make sure you are using RStudio. It will make your overall experience of using R significantly easier and more pleasant.
You can and should use the ?command syntax to read a description of what the commands + arguments mean. So for example ? phenoData, ?which
which(phenoData(lgg_data)$idh1_mutation_found=="Yes")
Try breaking things down, and trying stuff out to see what it's made of. Commands like head(), str(), table() and summary()
For example, try doing head(phenoData(lgg_data)) or str(phenoData(lgg_data)) or summary(phenoData(lgg_data)). What happens?
Then try head(phenoData(lgg_data)$idh1_mutation_found) and summary(phenoData(lgg_data)$idh1_mutation_found) and table(phenoData(lgg_data)$idh1_mutation_found)
Hint "idh1_mutation_found" is actually the name of a column in phenodata which contains a factor.
R is hard, and so is bioinformatics. There is no way around googling and trying stuff, sorry. Or do all of the edX Xseries on biological data analysis with R - but this will take you > month and not solve your direct problem.
There are number of resources where you can know about these commands.I have listed these A youtube video describing Deseq
Also you can get about working of these commands from the manual of DESEQ given at This link
And specifically if you want to learn R for bioinformatics then there are also bundle of resources to do that just google and write
R for Bioinformatics, R for NGS Data Analysis
And welcome to programming.
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Try this workflow from bioconductor, it will get you started and provides explanation on commands.