Quick Instructions:

##SETUP###
0a) raw data goes in input_data, genome goes in genome.  These are already done for demo data.  It's a good idea to name these <samplename>.fastq as in the demo file.
0b) run Setup.ba -e <your email>

##Step 1: Trimming##
1a) cd 1_trimming, read RunTrimRAD.sh -> it has notes built in!
   This step is meant to be done after doing fastqc, which is used to generate a "overrep.1%.list" file (one is provided for you).  Adaptors should be pasted into the "adaptors.fa" file, in fasta format.
1b) run the job!

##Step 2: Mapping##
2a) Read run 0_RunIndex.sh, this step takes a while, and has been done already for the demo data.
2b) Read and run 1_RunBWAwReadGroups.sh.  There is a lot of information in this file.  This will map a specific, hard coded file (here BDD17) in input_data/ to the genome in genome/.  But it only does one file.  This is to test that it works and looks okay with your data.
2c) Read and run 1_RunBWAwReadGroups_loop.sh.  This will loop through all files in input_data/ and map them to the genome in genome/.   
2d) Read and run 2_RunFilterandSortBams.sh.  This will filter poor mapping and sort the bams in preparation for merging.
2e) Read and run 3_RunMergeBams.sh. This will... merge the bams.

##Step 3: Variant Calling ##
3a) Read and run RunFreeBayes.sh

##Step 4: Filtering ##
This one is still TBD, but will be in R anyway.