$ git clone https://github.com/LANL-Bioinformatics/FaQCs.git
   $ cd FaQCs
   $ make
 
   # A FaQCs binary executable will be ready to use and it can 
   # be moved to user's or system PATH environment.

   $ conda install -c bioconda -c conda-forge faqcs

Usage: FaQCs [options] [-u unpaired.fastq] -p reads1.fastq reads2.fastq -d out_directory
Version 2.09
Input File(s):
	-u			<File> Unpaired reads
	-1			<File> First paired read file
	-2			<File> Second paired read file
Trim:
	--mode			"HARD" or "BWA" or "BWA_plus" (default BWA_plus)
				BWA trim is NOT A HARD cutoff! (see bwa's bwa_trim_read() function in bwaseqio.c)
	-q			<INT> Targets # as quality level (default 5) for trimming
	--5end			<INT> Cut # bp from 5 end before quality trimming/filtering
	--3end			<INT> Cut # bp from 3 end before quality trimming/filtering
	--adapter		<bool> Trim reads with illumina adapter/primers (default: no)
	--rate			<FLOAT> Mismatch ratio of adapters' length (default: 0.2, allow 20% mismatches)
	--polyA			<bool>  Trim poly A ( > 15 )
	--artifactFile		<File> additional artifact (adapters/primers/contaminations) reference file in fasta format
Filters:
	--min_L			<INT> Trimmed read should have to be at least this minimum length (default:50)
	--avg_q			<NUM> Average quality cutoff (default:0, no filtering)
	-n			<INT> Trimmed read has greater than or equal to this number of continuous base "N" will be discarded.
				(default: 2, "NN")
	--lc			<FLOAT> Low complexity filter ratio, Maximum fraction of mono-/di-nucleotide sequence  (default: 0.85)
	--phiX			<bool> Filter phiX reads (slow)
Q_Format:
	--ascii			Encoding type: 33 or 64 or autoCheck (default)
				Type of ASCII encoding: 33 (standard) or 64 (illumina 1.3+)
	--out_ascii		Output encoding. (default: 33)
Output:
	--prefix		<TEXT> Output file prefix. (default: QC)
	--stats			<File> Statistical numbers output file (default: prefix.stats.txt)
	-d			<PATH> Output directory.
Options:
	-t			<INT > # of CPUs to run the script (default:2 )
	--split_size		<INT> Split the input file into several sub files by sequence number (default: 1000000)
	--qc_only		<bool> no Filters, no Trimming, report numbers.
	--kmer_rarefaction	<bool>
				Turn on the kmer calculation. Turn on will slow down ~10 times. (default:Calculation is off.)
				(meaningless if -subset is too small)
	-m			<INT>     kmer for rarefaction curve (range:[2,31], default 31)
	--subset		<INT>   Use this nubmer x split_size for qc_only and kmer_rarefaction
				(default: 10,  10x1000000 SE reads, 20x1000000 PE reads)
	--discard		<bool> Output discarded reads to prefix.discard.fastq (default: 0, not output)
	--substitute		<bool> Replace "N" in the trimmed reads with random base A,T,C ,or G (default: 0, off)
	--trim_only		<bool> No quality report. Output trimmed reads only.
	--replace_to_N_q	<INT> Replace base G to N when below this quality score (default:0, off)
	--5trim_off		<bool> Turn off trimming from 5'end.
	--debug			<bool> Keep intermediate files
	--version		<bool> Print the version and exit