AMR pipeline using Abricate

#!/usr/bin/env bash
#Pipeline for bacterial analysis using Conda; trimming, assembly, species identification, and AMR genes
#Make sure you have FastQC and Quast installed on your computer; make sure you have a conda environment with trimmomatic, spades, mlst, and abricate
#Run in directory with a sub-directory for each set of fastq.gz files (i.e. just one R1 file and one R2 file in each directory); the name of each directory should contain the LIMS ID of the sample
#Output will be in output.tsv
#Edit paths as necessary

#First, activate Conda environment: conda activate bacterial

for dir in */
do
	cd $dir
	printf "${dir}" | cut -d / -f 1 >> output.tsv
	#FastQC (quality report)
	fastqc *1.fastq *2.fastq -o . --threads 10 --extract 
	#Pre-processing (trimming and filtering)
	##ILLUMINACLIP: Cut adapter and other illumina-specific sequences from the read.
	##LEADING: Cut bases off the start of a read, if below a threshold quality
	##TRAILING: Cut bases off the end of a read, if below a threshold quality
	##MINLEN: Drop the read if it is below a specified length
	trimmomatic PE -threads 10 *1.fastq *2.fastq p1.fq.gz up1.fq.gz p2.fq.gz up2.fq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10:2:keepBothReads LEADING:3 TRAILING:3 MINLEN:36
	#FastQC (quality report)
	fastqc -1 p1.fq.gz -2 p2.fq.gz -o . --threads 10 --extract 
	printf "\n\nFastQC Quality Report for Reads: Pre- and Post-Processing\n" >> output.tsv
	cat ./*/summary.txt >> output.tsv 
	#Assembly
	spades -1 p1.fq.gz -2 p2.fq.gz -o .
	#Quast (quality report)
	printf "\n\nQuast Quality Report for Consensus Genome\n" >> output.tsv
	python /home/mdungsmain/anaconda3/bin/quast.py -o . --threads 8 contigs.fasta 
	cat report.tsv >> output.tsv
	#Species identification (mlst)
	printf "\n\nSpecies Identification (mlst)" >> output.tsv
	mlst contigs.fasta >> output.tsv      
	#Identification of AMR genes
	printf "\n\n\nAMR Genes Identified\n\n"
	printf "\nNCBI Database\n" >> output.tsv
	abricate contigs.fasta --db ncbi >> output.tsv
	printf "\nCARD Database\n" >> output.tsv
	abricate contigs.fasta --db card >> output.tsv
	printf "\nResfinder Database\n" >> output.tsv
	abricate contigs.fasta --db resfinder >> output.tsv
	#Summary
	printf "\nSummary of AMR Genes of Interest\n" >> output.tsv
	awk -F"\t"  '$0 ~ "KPC" || $0 ~ "kpc" || $0 ~ "NDM" || $0 ~ "ndm" || $0 ~ "OXA" || $0 ~ "oxa" || $0 ~ "VIM" || $0 ~ "vim" || $0 ~ "IMP" || $0 ~ "imp" {printf $0 "\n"}' output.tsv >> output.tsv
	cd ..
done