@article {43,
	title = {Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects.},
	journal = {Nat Commun},
	volume = {9},
	year = {2018},
	month = {2018 Oct 02},
	pages = {4038},
	abstract = {<p>Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies.</p>},
	keywords = {Genome, Human, Human Genetics, Humans, Whole Genome Sequencing},
	issn = {2041-1723},
	doi = {10.1038/s41467-018-06159-4},
	author = {Regier, Allison A and Farjoun, Yossi and Larson, David E and Krasheninina, Olga and Kang, Hyun Min and Howrigan, Daniel P and Chen, Bo-Juen and Kher, Manisha and Banks, Eric and Ames, Darren C and English, Adam C and Li, Heng and Xing, Jinchuan and Zhang, Yeting and Matise, Tara and Abecasis, Gon{\c c}alo R and Salerno, Will and Zody, Michael C and Neale, Benjamin M and Hall, Ira M}
}
@article {34,
	title = {A synthetic-diploid benchmark for accurate variant-calling evaluation.},
	journal = {Nat Methods},
	volume = {15},
	year = {2018},
	month = {2018 Aug},
	pages = {595-597},
	abstract = {<p>Existing benchmark datasets for use in evaluating variant-calling accuracy are constructed from a consensus of known short-variant callers, and they are thus biased toward easy regions that are accessible by these algorithms. We derived a new benchmark dataset from the de novo PacBio assemblies of two fully homozygous human cell lines, which provides a relatively more accurate and less biased estimate of small-variant-calling error rates in a realistic context.</p>},
	keywords = {Algorithms, Benchmarking, Cell Line, Tumor, Databases, Genetic, Diploidy, Female, Genetic Variation, Genome, Human, Homozygote, Humans, Hydatidiform Mole, Pregnancy, Synthetic Biology, Uterine Neoplasms, Whole Genome Sequencing},
	issn = {1548-7105},
	doi = {10.1038/s41592-018-0054-7},
	author = {Li, Heng and Bloom, Jonathan M and Farjoun, Yossi and Fleharty, Mark and Gauthier, Laura and Neale, Benjamin and MacArthur, Daniel}
}
