text: user1196: I am doing a project that requires bench-marking the performance of computational tools for alignment and variant calling of human genome sequencing data. In particular I would like to establish benchmarks comparing the performance of GATK and ADAM/Avocado. 
  My main question is which genomic data-sets should I use as the input to the data processing pipeline. In Frank Nothaft's (author of ADAM and Avodaco) thesis he reports bench-marking the processing of NA12878 from the 1,000 genome's project in Avocado as compared to GATK's HalotypeCaller. He also reports benchmarking on 270 samples from the Simons Genome Diversity Data-set.
  I am interested in reproducing this portion of his work, but do not know where I can get a hold of these datasets. Where can I get a copy of the NA12878 genome (BAM file) and also were can I get aligned samples from Simons Genome Diversity Data-set? 
  
  user37: NA12878
  
  My recommendation: download raw reads from Illumina BaseSpace and do alignment yourself. Aligning ~40X worth of human reads takes overnight with ~16 CPU cores.
  You can acquire Platinum Genome data from ENA. There is a BAM available for download, but that was done by Illumina's own aligner against a wrong reference genome. You'd better do alignment by yourself. Another problem with this dataset is it is too good to be representative. Modern data are worse.
  GIAB provides BAMs here:
  ftp://ftp-trace.ncbi.nih.gov/giab/ftp/data/NA12878/NIST_NA12878_HG001_HiSeq_300x/
  
  It is not "typical", either.
  
  SGDP
  
  Instructions on downloading SGDP BAMs are available on this page, in particular this Word document. Warning: you need ~30TB disk space for these BAMs. I also heard it is tricky to download data.
  There is apparently a mirror from cancer genomics cloud. I don't know how easy it is to access.
  
  
original_text: 1196: <p>I am doing a project that requires bench-marking the performance of computational tools for alignment and variant calling of human genome sequencing data. In particular I would like to establish benchmarks comparing the performance of <a href="https://software.broadinstitute.org/gatk/" rel="nofollow noreferrer">GATK</a> and <a href="https://github.com/bigdatagenomics/adam" rel="nofollow noreferrer">ADAM</a>/<a href="https://github.com/bigdatagenomics/avocado" rel="nofollow noreferrer">Avocado</a>. </p>
  
  <p>My main question is which genomic data-sets should I use as the input to the data processing pipeline. In Frank Nothaft's (author of ADAM and Avodaco) <a href="https://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-204.html" rel="nofollow noreferrer">thesis</a> he reports bench-marking the processing of NA12878 from the 1,000 genome's project in Avocado as compared to GATK's HalotypeCaller. He also reports benchmarking on 270 samples from the Simons Genome Diversity Data-set.</p>
  
  <p>I am interested in reproducing this portion of his work, but do not know where I can get a hold of these datasets. Where can I get a copy of the NA12878 genome (BAM file) and also were can I get aligned samples from Simons Genome Diversity Data-set? </p>
   37: <h3>NA12878</h3>
  
  <ul>
  <li><p>My recommendation: download raw reads from <a href="https://basespace.illumina.com/home/index" rel="nofollow noreferrer">Illumina BaseSpace</a> and do alignment yourself. Aligning ~40X worth of human reads takes overnight with ~16 CPU cores.</p></li>
  <li><p>You can acquire <a href="https://www.illumina.com/platinumgenomes.html" rel="nofollow noreferrer">Platinum Genome</a> data <a href="https://www.ebi.ac.uk/ena/data/view/ERX168836" rel="nofollow noreferrer">from ENA</a>. There is a BAM available for download, but that was done by Illumina's own aligner against a wrong reference genome. You'd better do alignment by yourself. Another problem with this dataset is it is too good to be representative. Modern data are worse.</p></li>
  <li><p>GIAB provides BAMs here:</p>
  
  <pre><code>ftp://ftp-trace.ncbi.nih.gov/giab/ftp/data/NA12878/NIST_NA12878_HG001_HiSeq_300x/
  </code></pre>
  
  <p>It is not "typical", either.</p></li>
  </ul>
  
  <h3>SGDP</h3>
  
  <ul>
  <li><p>Instructions on downloading SGDP BAMs are available <a href="https://www.simonsfoundation.org/simons-genome-diversity-project/" rel="nofollow noreferrer">on this page</a>, in particular <a href="http://simonsfoundation.s3.amazonaws.com/share/SCDA/datasets/2014_11_12/StepstodownloadtheSGDPdataset_v4.docx" rel="nofollow noreferrer">this Word document</a>. Warning: you need ~30TB disk space for these BAMs. I also heard it is tricky to download data.</p></li>
  <li><p>There is apparently a mirror <a href="https://docs.cancergenomicscloud.org/v1.0/docs/simons-genome-diversity-project-sgdp-dataset" rel="nofollow noreferrer">from cancer genomics cloud</a>. I don't know how easy it is to access.</p></li>
  </ul>
  