text: user9118: My goal is to generate a diploid consensus genome. By "diploid consensus", I mean that I want to merge all supporting reads for a genomic region into a single haplome such that the resulting sam file contains TWO sets of reads, one from each haplome.
  I have Illumina short-read files from the NCBI's SRA. These short-reads were obtained from a diploid species.
  I am worried that, by simply using Picard's MarkDuplicates with the "REMOVE_DUPLICATES" option set to "TRUE", I will retain only the homolog with the highest quality and output a haploid version of my genome.
  Here is my current workflow:
  
  ## Map Illumina reads to the reference genome. Include read IDs
  bwa mem -M -R '@RG\tID:BioSample.LibraryName\tSM:BioSample\tLB:LibraryName\tPU:SingleFlowcell.SingleLane\tPL:ILLUMINA\t' reference.fasta SRR[number]_1.fastq SRR[number]_2.fastq > SRR[number].sam  
  
  ## Sort Illumina reads by coordinate
  java -jar $EBROOTPICARD/picard.jar SortSam I=SRR[number].sam O=sorted_SRR[number].sam CREATE_INDEX=true SORT_ORDER=coordinate TMP_DIR=$TMPDIR
  
  ## Remove duplicate reads from sam file
  ## *Note: How do I remove sampling error reads?
  java -jar $EBROOTPICARD/picard.jar MarkDuplicates REMOVE_DUPLICATES=true REMOVE_SEQUENCING_DUPLICATES=true I= 'sorted_SRR[number].sam' O= nodup_SRR[number].sam METRICS_FILE= metrics_SRR[number].txt TMP_DIR=$TMPDIR
  
  ## Convert duplicate-free sam file to bam file
  samtools view -S -b nodup_SRR[number].sam > nodup_SRR[number].bam 
  
  ## Re-align reads around indels to reduce slippage.
  gatk LeftAlignIndels -R reference.fasta -I nodup_SRR[number].bam -O aligned_SRR[number].bam 
  
  Does anyone know of a program which will whittle my sam files down to ONLY two homologs per region?
  
  user1140: How to separate reads, one for each reference haplotype.
  
  Map all the reads against the reference genome
  Use GATK to call SNPs
  Use GATK tool [FastaAlternateReferenceMaker][1] to build the alternative reference
  You now have the two "haploid references" (quotes needed because you have to take into account that they will not necessarily reflect the exact haplotypic structure, it could be a mix of the two haplotypes)
  Align the reads against the two references, and attribute each read to the reference to which they map better. My colleagues developed for a different purpose (detection of Allelic Imbalance) a pipeline that includes the step for determining to which of two references a read belongs. The tool is called [BayesASE][2]
  
  In general you may study all the work that has been done in the field of allelic imbalance and allele specific expression, where this problem has been encountered and solved.
  [1]: https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker
  [2]: https://github.com/McIntyre-Lab/BayesASE
  
original_text: 9118: <p>My goal is to generate a diploid consensus genome. By &quot;diploid consensus&quot;, I mean that I want to merge all supporting reads for a genomic region into a single haplome such that the resulting sam file contains TWO sets of reads, one from each haplome.</p>
  <p>I have Illumina short-read files from the NCBI's SRA. These short-reads were obtained from a diploid species.</p>
  <p>I am worried that, by simply using Picard's MarkDuplicates with the &quot;REMOVE_DUPLICATES&quot; option set to &quot;TRUE&quot;, I will retain only the homolog with the highest quality and output a haploid version of my genome.
  Here is my current workflow:</p>
  <pre><code>
  ## Map Illumina reads to the reference genome. Include read IDs
  bwa mem -M -R '@RG\tID:BioSample.LibraryName\tSM:BioSample\tLB:LibraryName\tPU:SingleFlowcell.SingleLane\tPL:ILLUMINA\t' reference.fasta SRR[number]_1.fastq SRR[number]_2.fastq &gt; SRR[number].sam  
  
  ## Sort Illumina reads by coordinate
  java -jar <span class="math-container">$EBROOTPICARD/picard.jar SortSam I=SRR[number].sam O=sorted_SRR[number].sam CREATE_INDEX=true SORT_ORDER=coordinate TMP_DIR=$</span>TMPDIR
  
  ## Remove duplicate reads from sam file
  ## *Note: How do I remove sampling error reads?
  java -jar <span class="math-container">$EBROOTPICARD/picard.jar MarkDuplicates REMOVE_DUPLICATES=true REMOVE_SEQUENCING_DUPLICATES=true I= 'sorted_SRR[number].sam' O= nodup_SRR[number].sam METRICS_FILE= metrics_SRR[number].txt TMP_DIR=$</span>TMPDIR
  
  ## Convert duplicate-free sam file to bam file
  samtools view -S -b nodup_SRR[number].sam &gt; nodup_SRR[number].bam 
  
  ## Re-align reads around indels to reduce slippage.
  gatk LeftAlignIndels -R reference.fasta -I nodup_SRR[number].bam -O aligned_SRR[number].bam 
  </code></pre>
  <p>Does anyone know of a program which will whittle my sam files down to ONLY two homologs per region?</p>
   1140: <p>How to separate reads, one for each reference haplotype.</p>
  <ol>
  <li>Map all the reads against the reference genome</li>
  <li>Use GATK to call SNPs</li>
  <li>Use GATK tool [FastaAlternateReferenceMaker][1] to build the alternative reference</li>
  <li>You now have the two &quot;haploid references&quot; (quotes needed because you have to take into account that they will not necessarily reflect the exact haplotypic structure, it could be a mix of the two haplotypes)</li>
  <li>Align the reads against the two references, and attribute each read to the reference to which they map better. My colleagues developed for a different purpose (detection of Allelic Imbalance) a pipeline that includes the step for determining to which of two references a read belongs. The tool is called [BayesASE][2]</li>
  </ol>
  <p>In general you may study all the work that has been done in the field of allelic imbalance and allele specific expression, where this problem has been encountered and solved.
  [1]: <a href="https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker" rel="nofollow noreferrer">https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker</a>
  [2]: <a href="https://github.com/McIntyre-Lab/BayesASE" rel="nofollow noreferrer">https://github.com/McIntyre-Lab/BayesASE</a></p>
  