Debated even posting this, as its hardly unexpected and certainly not a question.
None the less - I thought others might possibly be doing this, or wondering about how it works out.
I ran Salmon using a Salmon index to map reads from a 50 bp single ended non-directional RNAseq read set, from 4 sample conditions with each condition having 4 biological replicates. I took the quant.sf file and wrote a script to sum transcript counts as floating point values to the gene level, then truncated to an integer and brought all that into DESeq2. DESseq2 was perfectly happy with this data, I even went so far as to reproduce most of the figures contained in the manual just to ensure it was behaving "normally" and indeed, all was well, or at least produced figures that had nearly identical properties to those illustrated in the DESeq2 guide. I will be using this pipeline again. The Salmon output is very easy to script on and it was not much work to get this all up and running and combined with DESeq2 its appearing to be a pretty dang quick way to get RNAseq differential expression analyses accomplished.
Thanks!