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Adam Auton

Other affiliations: Broad Institute, Cornell University, University of Oxford  ...read more
Bio: Adam Auton is an academic researcher from Albert Einstein College of Medicine. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 47, co-authored 94 publications receiving 51799 citations. Previous affiliations of Adam Auton include Broad Institute & Cornell University.


Papers
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Journal ArticleDOI
TL;DR: Results suggest that both rare and common DNA variations in PNPLA3 and SAMM50 may be correlated with NAFLD in this small population study, while commonDNA variations in CHUK and ERLIN1 may have a protective interaction.
Abstract: We explored potential genetic risk factors implicated in nonalcoholic fatty liver disease (NAFLD) within a Caribbean-Hispanic population in New York City. A total of 316 individuals including 40 subjects with biopsy-proven NAFLD, 24 ethnically matched non-NAFLD controls, and a 252 ethnically mixed random sampling of Bronx County, New York were analyzed. Genotype analysis was performed to determine allelic frequencies of 74 known single-nucleotide polymorphisms (SNPs) associated with NAFLD risk based on previous genome-wide association study (GWAS) and candidate gene studies. Additionally, the entire coding region of PNPLA3, a gene showing the strongest association to NAFLD was subjected to Sanger sequencing. Results suggest that both rare and common DNA variations in PNPLA3 and SAMM50 may be correlated with NAFLD in this small population study, while common DNA variations in CHUK and ERLIN1, may have a protective interaction. Common SNPs in ENPP1 and ABCC2 have suggestive association with fatty liver, but with less compelling significance. In conclusion, Hispanic patients of Caribbean ancestry may have different interactions with NAFLD genetic modifiers; therefore, further investigation with a larger sample size, into this Caribbean-Hispanic population is warranted.

16 citations

Journal ArticleDOI
TL;DR: In this paper, the Templated positional Burrows-Wheeler transform (TPBWT) is proposed to make fast IBD estimates robust to genotype and phasing errors. But the authors highlight the fragility of most phase-aware IBD inference methods; the accuracy of IBD estimate can be highly sensitive to the quality of haplotype phasing.
Abstract: Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors, we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally, we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale data sets with millions of samples. Furthermore, we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis, exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for noncommercial use in the code repository (https://github.com/23andMe/phasedibd, last accessed January 11, 2021).

16 citations

Posted ContentDOI
17 Jun 2016-bioRxiv
TL;DR: Exome sequences from 3,222 British-Pakistani individuals with high parental relatedness are used to estimate exome mutation rates, finding frequent recurrence of mutations at polymorphic CpG sites, and an increase in C to T mutations in the Pakistani population compared to Europeans, suggesting that mutational processes have evolved rapidly between human populations.
Abstract: Heterozygous mutations within homozygous sequences descended from a recent common ancestor offer a way to ascertain de novo mutations (DNMs) across multiple generations. Using exome sequences from 3,222 British-Pakistani individuals with high parental relatedness, we estimate a mutation rate of 1.45 ± 0.05 × 10 -8 per base pair per generation in autosomal coding sequence, with a corresponding non-crossover gene conversion rate of 8.75 ± 0.05 × 10 -6 per base pair per generation. This is at the lower end of exome mutation rates previously estimated in parent-offspring trios, suggesting that post-zygotic mutations contribute little to the human germline mutation rate. We found frequent recurrence of mutations at polymorphic CpG sites, and an increase in C to T mutations in a 59 CCG 39 → 59 CTG 39 context in the Pakistani population compared to Europeans, suggesting that mutational processes have evolved rapidly between human populations.

15 citations

Posted ContentDOI
24 Sep 2019-bioRxiv
TL;DR: In this article, a framework for repurposing data from Electronic Health Records (EHRs) in concert with genomic data to explore enrichment of disease within sub-populations was proposed.
Abstract: Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens specific to sub-populations. Here we propose a framework for repurposing data from Electronic Health Records (EHRs) in concert with genomic data to explore enrichment of disease within sub-populations. Using data from a diverse biobank in New York City, we genetically identified 17 sub-populations, and noted the presence of genetic founder effects in 7. By then linking community membership to the EHR, we were able to identify over 600 health outcomes that were statistically enriched within a specific population, with many representing known associations, and many others being novel. This work reinforces the utility of linking genomic data to EHRs, and provides a framework towards fine-scale monitoring of population health.

15 citations

Posted ContentDOI
26 Jul 2016-bioRxiv
TL;DR: It is shown that missing mutations are a significant feature of genomic datasets and imply additional fine-tuning of bioinformatics pipelines is needed, and a phylogeny-aware tool is designed which can be used to quantify the FN rate for haploid genomic experiments, without additional generation of validation data.
Abstract: Author(s): Bobo, Dean; Lipatov, Mikhail; Rodriguez-Flores, Juan; Auton, Adam; Henn, Brenna | Abstract: Short-read, next-generation sequencing (NGS) is now broadly used to identify rare or de novo mutations in population samples and disease cohorts. However, NGS data is known to be error-prone and post-processing pipelines have primarily focused on the removal of spurious mutations or “false positives” for downstream genome datasets. Less attention has been paid to characterizing the fraction of missing mutations or “false negatives” (FN). Here we interrogate several publically available human NGS autosomal variant datasets using corresponding Sanger sequencing as a truth-set. We examine both low-coverage Illumina and high-coverage Complete Genomics genomes. We show that the FN rate varies between 3%-18% and that false-positive rates are considerably lower (l3%) for publically available human genome callsets like 1000 Genomes. The FN rate is strongly dependent on calling pipeline parameters, as well as read coverage. Our results demonstrate that missing mutations are a significant feature of genomic datasets and imply additional fine-tuning of bioinformatics pipelines is needed. To address this, we design a phylogeny-aware tool [PhyloFaN] which can be used to quantify the FN rate for haploid genomic experiments, without additional generation of validation data. Using PhyloFaN on ultra-high coverage NGS data from both Illumina HiSeq and Complete Genomics platforms derived from the 1000 Genomes Project, we characterize the false negative rate in human mtDNA genomes. The false negative rate for the publically available mtDNA callsets is 17-20%, even for extremely high coverage haploid data.

14 citations


Cited by
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Journal ArticleDOI
TL;DR: Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

37,898 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

12,661 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an approach for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

10,798 citations

Journal ArticleDOI
TL;DR: VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API.
Abstract: Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API. Availability: http://vcftools.sourceforge.net Contact: [email protected]

10,164 citations