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title | demultiplexing |
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collapse | true |
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#look at the set of barcodes included for our samples
lesscat barcodes_Lib1.tsv
#check the reads
grep CATG Lib01_R1.fastq | head
#check where these are in our reads
grep "^TCGAT" Lib01_R1.fastq | wc -l
grep "^CGATC" Lib01_R1.fastq | wc -l
grep "^AACCA" Lib01_R1.fastq | wc -l
grep "^GCATG" Lib01_R1.fastq | wc -l
#make a directory to put the resulting sample fastq files into
mkdir sample_fastqs
#look at the documentation for process_radtags
./process_radtags -h
#execute the command to process the rad data
./process_radtags -i 'fastq' -1 Lib01_R1.fastq -2 Lib01_R2.fastq -o ./sample_fastqs/ -b barcodes_Lib1.tsv --inline_index -e 'nlaIII' -r --disable_rad_check |
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#check out our reference
less stickleback_chrom3.fasta
#how many sequences are there?
grep "^>" stickleback_chrom3.fasta | wc -l
#index the reference
module load bwa
bwa index stickleback_chrom3.fasta
#run mapping
bwa mem stickleback_chrom3.fasta sample_fastqs/sample_AACCA-AGCGAC.1.fq sample_fastqs/sample_AACCA-AGCGAC.2.fq > sampleA.sam
bwa mem stickleback_chrom3.fasta sample_fastqs/sample_CGATC-AGCGAC.1.fq sample_fastqs/sample_CGATC-AGCGAC.2.fq > sampleB.sam
bwa mem stickleback_chrom3.fasta sample_fastqs/sample_GCATG-AGCGAC.1.fq sample_fastqs/sample_GCATG-AGCGAC.2.fq > sampleC.sam
bwa mem stickleback_chrom3.fasta sample_fastqs/sample_TCGAT-AGCGAC.1.fq sample_fastqs/sample_TCGAT-AGCGAC.2.fq > sampleD.sam
#assess mapping efficiency
module load samtools
samtools flagstat sampleA.sam > flagStatRes_sampleA.txt
samtools flagstat sampleB.sam > flagStatRes_sampleB.txt
samtools flagstat sampleC.sam > flagStatRes_sampleC.txt
samtools flagstat sampleD.sam > flagStatRes_sampleD.txt
#these results are not spectacular.
#80% mapping efficiency is OK, but the low rate of properly paired reads is disapointingdissapointing.
#convert the sam files to bam files
samtools sort sampleA.sam -O SAMBAM -o sampleA.bam
samtools sort sampleB.sam -O SAMBAM -o sampleB.bam
samtools sort sampleC.sam -O SAMBAM -o sampleC.bam
samtools sort sampleD.sam -O SAMBAM -o sampleD.bam |
Genotyping
Now genotype the samples with mpileup.
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#index the reference for samtools
module load samtools
samtools faidx stickleback_chrom3.fasta
#make a list of the bam files
ls *.bam > my_bamfiles.txt
#run mpileup
samtools mpileup -f stickleback_chrom3.fasta -t DP,AD,ADF,ADR,SP -u -b my_bamfiles.txt > mpileup_results.bcf
#now call genotypes from the mpileup results
bcftools call -vmO v -o raw_calls.vcf mpileup_results.bcf |
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title | quality filtering |
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collapse | true |
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#how many raw genotyped sites to be have?
vcftools --vcf raw_calls.vcf
#After filtering, kept 4 out of 4 Individuals
#After filtering, kept 14559 out of a possible 14559 Sites
#now perform basic quality filtering on raw calls
bcftools filter --exclude 'QUAL < 30' raw_calls.vcf | bcftools view > filt0.vcf
#check the new quality checked vcf
vcftools --vcf filt0.vcf
#Additionally, you can filter on representation among samples, allele frequency, and other options with VCFtools
#Filter for biallelic sites variants
#genotyped in 75% of samples,
#with at least two reads covering the site
vcftools --vcf filt0.vcf --max-alleles 2 --max-missing 0.75 --minDP 2 --recode --out filt2
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Complete.