I want to transform a TCGA mRNA expression matrix (in linear data format) to log2-ratios and then run a feature (gene) selection, selecting the 1000 most variant genes (genes with higher standard deviation across samples). The workflow is the following:

1. Select "good" genes before log2ratio (genes each with median signal at least t in p% of samples);
2. On selected genes, run log2ratio, dividing each gene by its median signal and then log2-transforming the result matrix;
3. Select the 1000 most variant genes along all samples.

How do I select t and p?
There is not a general solution to select "t" and "p". Such choices are largely arbitrary. Furthermore, for an array platform, if one assumes that "t" has something to do with "expressed", the value for "t" will differ for each probe on the array.

Since you are ultimately going to filter based on variance, I'd suggest starting with your median-centered, log-transformed data and simply choose the top 1000 most variable genes.