Calculate corrected theta from resequencing data: Difference between revisions

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This procedure will estimate theta (nucleotide diversity) based on re-sequencing data. The method is describe in [http://www.biomedcentral.com/1471-2164/14/148 Esteve-Codina et al.]
<source lang ='bash'>
<source lang ='bash'>
#!/bin/bash
#!/bin/bash
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#SBATCH --ntasks=1
#SBATCH --ntasks=1
#SBATCH --nodes=1
#SBATCH --nodes=1
#SBATCH --constraint=normalmem
#SBATCH --constraint=4gpercpu
#SBATCH --output=output_%j.txt
#SBATCH --output=output_%j.txt
#SBATCH --error=error_output_%j.txt
#SBATCH --error=error_output_%j.txt
#SBATCH --job-name=ngstheta
#SBATCH --job-name=ngstheta
#SBATCH --partition=ABGC_Research
module load samtools/0.1.19
module load samtools/0.1.19
VAR=`gunzip -c /lustre/nobackup/WUR/ABGC/shared/Pig/vars_hjm_newbuild10_2/vars-flt_$1-final.txt.gz  | cut -f8 | head -1000000 | sort | uniq -c | sed 's/^ \+//' | sed 's/ \+/\t/' | sort -k1 -nr | head -1 | cut -f2`
VAR=`gunzip -c /lustre/nobackup/WUR/ABGC/shared/Pig/vars_hjm_newbuild10_2/vars-flt_$1-final.txt.gz  | cut -f8 | head -1000000 | sort | uniq -c | sed 's/^ \+//' | sed 's/ \+/\t/' | sort -k1 -nr | head -1 | cut -f2`
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</source>
</source>


The script can be submitted using <code>sbatch</code> using the following code, assuming that the names of the individuals are listed in a file called <code>individuals.txt</code>.
<source lang='bash'>
<source lang='bash'>
INDS=`cat bams.txt | grep -v LB01`
INDS=`cat individuals.txt`
for IND in $INDS; do sbatch nucdiv_pipeline.sh $IND; done
for IND in $INDS; do sbatch nucdiv_pipeline.sh $IND; done
</source>
</source>


<source lang = 'R'>
Average values for Theta were then extracted with the following R-srcript:
<source lang = 'rsplus'>
files=list.files(pattern="wintheta")
files=list.files(pattern="wintheta")
a <- data.frame("file" = character(), "theta_het" = numeric())
a <- data.frame("file" = character(), "theta_het" = numeric())
for (file1 in files){x <- read.table(file1,header=T); mn=mean(x$THETA_HET[x$BP>20000 & x$CHR != 'chrUN_nr']); print(paste(file1,mn,sep="  "));a<- rbind(a,data.frame("file"=file1,"theta_het"=mn))}
for (file1 in files){
  x <- read.table(file1,header=T);  
  mn=mean(x$THETA_HET[x$BP>20000 & x$CHR != 'chrUN_nr' & x$CHR != 'Ssc10_2_X']);  
  print(paste(file1,mn,sep="  "));
  a<- rbind(a,data.frame("file"=file1,"theta_het"=mn))
}
write.table(x=a,file="theta_het_results.txt")
write.table(x=a,file="theta_het_results.txt")
</source>
</source>

Latest revision as of 16:00, 15 July 2019

This procedure will estimate theta (nucleotide diversity) based on re-sequencing data. The method is describe in Esteve-Codina et al.


<source lang ='bash'>

  1. !/bin/bash
  2. SBATCH --time=10000
  3. SBATCH --mem=4000
  4. SBATCH --ntasks=1
  5. SBATCH --nodes=1
  6. SBATCH --constraint=4gpercpu
  7. SBATCH --output=output_%j.txt
  8. SBATCH --error=error_output_%j.txt
  9. SBATCH --job-name=ngstheta

module load samtools/0.1.19 VAR=`gunzip -c /lustre/nobackup/WUR/ABGC/shared/Pig/vars_hjm_newbuild10_2/vars-flt_$1-final.txt.gz | cut -f8 | head -1000000 | sort | uniq -c | sed 's/^ \+//' | sed 's/ \+/\t/' | sort -k1 -nr | head -1 | cut -f2` let MAX=2*VAR echo "$1 max_depth is $MAX" MIN=$(( $VAR / 3 )) if [ $MIN -lt 5 ]; then MIN=4; fi

echo "$1 min_depth is $MIN" samtools mpileup -uf /lustre/nobackup/WUR/ABGC/shared/Pig/Sscrofa_build10_2/FASTA/Ssc10_2_chromosomes.fa /lustre/nobackup/WUR/ABGC/shared/Pig/BAM_files_hjm_newbuild10_2/$1_rh.bam | bcftools view -bvcg - > $1.mig.bcf bcftools view $1.mig.bcf | vcfutils.pl varFilter -d$MIN -D$MAX > $1.mig.vcf awk '$6 >= 20' $1.mig.vcf > $1.miguel.vcf samtools mpileup -Bq 20 -d 50000 /lustre/nobackup/WUR/ABGC/shared/Pig/BAM_files_hjm_newbuild10_2/$1_rh.bam | perl covXwin-v3.1.pl -v $1.miguel.vcf -w 50000 -d $MIN -m $MAX -b /lustre/nobackup/WUR/ABGC/shared/Pig/BAM_files_hjm_newbuild10_2/$1_rh.bam | ./ngs_theta -d $MIN -m $MAX > $1.wintheta </source>

The script can be submitted using sbatch using the following code, assuming that the names of the individuals are listed in a file called individuals.txt. <source lang='bash'> INDS=`cat individuals.txt` for IND in $INDS; do sbatch nucdiv_pipeline.sh $IND; done </source>

Average values for Theta were then extracted with the following R-srcript: <source lang = 'rsplus'> files=list.files(pattern="wintheta") a <- data.frame("file" = character(), "theta_het" = numeric()) for (file1 in files){

  x <- read.table(file1,header=T); 
  mn=mean(x$THETA_HET[x$BP>20000 & x$CHR != 'chrUN_nr' & x$CHR != 'Ssc10_2_X']); 
  print(paste(file1,mn,sep="  "));
  a<- rbind(a,data.frame("file"=file1,"theta_het"=mn))

} write.table(x=a,file="theta_het_results.txt") </source>