## What is your prior experience in this discipline?    
All of my experience comes from stops and starts in lab, mostly from mimmicking what has already been done by others but nothing 'from scratch'.  

## What do you hope to get out of this class?    
I hope to gain a broader pipeline understanding, and with it a comfort in and a greater familiartiy with the process from start to finish.  

## This class is strongly rooted in an independent project related to genomic analyses. What specific project do you have in mind? If you do not have any data or preference, data can be provided / aquired. If you do not have a specfic project, what approach would you like to master as part of this class?  
There are three Mytilus e datasets on NCBI that are from experiments looking at chemical, biological, and environmental stressors. I am going to use these datasets to answer how common or uncommon the physiological response is dependent on contaminant.  

## What are two things you found most useful from the reading?  
Very basically, the file structure seems intuitive on its face but I always end up defaulting to a less disciplined model. Something as simple as keeping raw data separated from maniulated data is a good reminder that mistakes are made when we get sloppy with structure. The same is true for 'path' structures in reproducible work - it is easy to just use the whole path and go back later when the truth is you never will. The introduction to command line was a great refresher as command line always makes me feel like I don't know where I am no matter how many times I pwd.