Input and IgG control for different things in RIP-seq.

Input controls for how expressed each RNA is (you expect to see more signal from a highly expressed RNA than a lowly expressed one), as well as various sequencing bias' (GC content, % uniqueness etc); whereas IgG controls mainly for the specificity of your antibody and the effectiveness of the pull down.

Subtraction on a linear scale is unlikely to be the correct answer as this sort of data is usually ratiometric in nature, so you want to be dividing (or subtracting on a log scale).

For most purposes input is probably the best control, but you will see some sequences that interact with IgG, and the suspcian will be that if those sequences interact with your IP, it is because of non-specific effects.

For a simple analysis I would put all of the counts as raw counts into DESeq. I would that use DEseq to find transcripts where there is an enrichment in IP over input by effectively doing a DE analysis between IP and input. You could deal with the IgG in two ways - either do the same DE for IgG and input, and disregard any genes in that analysis from the IP analysis, or you could go whole hog and do a differences-in-differences test. I'm usually a fan of differences in differences, but given the likely big difference in read conuts between IP and IgG, I think i'd go for the first option here.

When you are doing your Ctrl and Treated anslysis, I would go for differences-in-differences though. Becuase the non-specific binding should be the same in both treated and ctrl, rather than doing an IgG control here, I would do IP-Cntrl, IP-treated, input-cntrl, input-treated.

I would then use DESeq to look at the interaction term (or coding the contrast (IP.Treated - input.treated) - (IP.cntrl-input.cntrl)). If you don't do this, you risk just identifying genes where the expression has increased, and the binding of the protein is increased because of this, not because the protein actaully binds tighter.