Hello all,

**Introduction**

I am a recent graduate working for a Public Health Laboratory. I'm relatively new to bioinformatics, and most of what I know is based around NGS analysis. My lab director loves to challenge me. He wants to know different ways NGS (we have a MiSeq) could be implemented in our lab as an outbreak investigation tool. 

I am aiming to do a study of Carbapenem-Resistant Enterobacteriaceae (CRE). The main goal is to be able to receive a CRE sample and use NGS to detect the genes (beta-lactamases) that are responsible. The idea is to be able to run quick analysis, while also compiling genetic information that could be used to connect the dots in an outbreak investigation (Phylogeny). 


**What I already Know**

 - The genes that I am looking for can be found within the bacterial chromosome, or within its plasmids
 - For each gene, primers need to be designed for them.

**The Actual Questions**

First: 
If I wish to take the whole-genome-sequencing approach, how would I be able to tell which parts of my output (FastQ) are plasmids vs. which parts are chromosome?

Second:
If I didn't want to do whole-genome, would it be possible to only sequence the genes that I'm looking for (if they are there)? And if so, how would I do it?

**Open for Discussion**

If anyone has any suggestions, solutions, or wishes to point me in a direction where I can learn more, please let me know. It would be a huge help, and is deeply appreciated.

Edit: ***Solution Found***

Thanks to those who commented before, I know have a better understanding on how this all works. Also, it put me on a path to find an example of how this type of experiment is done in a clinical laboratory. You can find the study [here][1].


  [1]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4097710/#!po=50.0000
1) From WGS data, chromosome vs episome can be distinguished by copy number (reflected in differences in read depth). With appropriate data, you can also assemble the genomes and distinguish the two by contigs.

2) Search for 'amplicon sequencing'. Note that the MiSeq, at 10M+ reads/run, is overkill unless you're barcoding 1000s of samples.