@article {36,
	title = {Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases.},
	journal = {Nat Genet},
	volume = {50},
	year = {2018},
	month = {2018 May},
	pages = {693-698},
	abstract = {<p>Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the {\textquoteright}no horizontal pleiotropy{\textquoteright} assumption can cause severe bias in MR. We developed the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test to identify horizontal pleiotropic outliers in multi-instrument summary-level MR testing. We showed using simulations that the MR-PRESSO test is best suited when horizontal pleiotropy occurs in <50\% of instruments. Next we applied the MR-PRESSO test, along with several other MR tests, to complex traits and diseases and found that horizontal pleiotropy (i) was detectable in over 48\% of significant causal relationships in MR; (ii) introduced distortions in the causal estimates in MR that ranged on average from -131\% to 201\%; (iii) induced false-positive causal relationships in up to 10\% of relationships; and (iv) could be corrected in some but not all instances.</p>},
	keywords = {Disease, Genetic Pleiotropy, Genetic Predisposition to Disease, Genetic Variation, Humans},
	issn = {1546-1718},
	doi = {10.1038/s41588-018-0099-7},
	author = {Verbanck, Marie and Chen, Chia-Yen and Neale, Benjamin and Do, Ron}
}
@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}
}
