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#navigate to the directory
cd denovo_2bRAD


#look at starting trimmed fastq files
ls *_trimmed.trimfastq
 
        sampleA.trim  sampleB.trim  sampleC.trim
 
#run uniquerOne.pl
#(this is analogous to making 'stacks' in STACKS (Fig1A Catchen et al. (2011))
#finds the unique RAD tags from each fastq
 
uniquerOne.pl sampleA_trimmed.trimfastq > sampleA.trim.uni
uniquerOne.pl sampleB_trimmed.trimfastq > sampleB.trim.uni
uniquerOne.pl sampleC_trimmed.trimfastq > sampleC.trim.uni
 
# merging uniqued files
#(Fig1B Catchen et al. (2011))
mergeUniq.pl uni minDP=2 >mydataMerged.uniq
 
#generates a merged set of unique tags:
        mergedUniqTags.fasta
 
# clustering allowing for up to 3 mismatches (-c 0.91); the most abundant sequence becomes reference
#This is equivalent to calling loci (Fig1C-D Catchen et al. (2011))
module load cd-hit
cd-hit-est -i mergedUniqTags.fasta -o cdh_alltags.fas -aL 1 -aS 1 -g 1 -c 0.91 -M 0 -T 0


#now we have called de novo loci based on the tags (70758 total)
#assemble them into an artificial reference for re-mapping and genotyping
concatFasta.pl fasta=cdh_alltags.fas num=8
 
#index the artificial reference with bowtie
module load bowtie
bowtie2-build cdh_alltags_cc.fasta cdh_alltags_cc.fasta
 
#now map the reads back to the artificial reference
 create mapping commands using a for loop
>mappingCommands
for file in *_trimmed.fastq
 do echo "bowtie2 --no-unal -x cdh_alltags_cc.fasta -U $file -S ${file/_trimmed.fastq/}.sam -p 12">>mappingCommands
done


#look at the mapping commands
cat mappingCommands


#returns:
	bowtie2 --no-unal -x cdh_alltags_cc.fasta -U sampleC_trimmed.trimfastq -S sampleC.trim.bt2.sam
sam -p 12 &
	bowtie2 --no-unal -x cdh_alltags_cc.fasta -U sampleB_trimmed.trimfastq -S sampleB.trim.bt2.sam -p 12 &
	bowtie2 --no-unal -x cdh_alltags_cc.fasta -U sampleA_trimmed.trimfastq -S sampleA.trim.bt2.sam
 
#The sam -p 12 &


#These will use bowtie to map the reads back to the clustered loci we generated from them
#copy the commands and paste them to execute
#The resulting alignment files can now be used for whichever genotyping method you prefer