8 results on '"Darren C. Ames"'
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2. Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example.
- Author
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Samuel J. Aronson, Lawrence J. Babb, Darren C. Ames, Richard A. Gibbs, Eric Venner, John J. Connelly, Keith Marsolo, Chunhua Weng, Marc S. Williams, Andrea L. Hartzler, Wayne H. Liang, James D. Ralston, Emily Beth Devine, Shawn N. Murphy, Christopher G. Chute, Pedro J. Caraballo, Iftikhar J. Kullo, Robert R. Freimuth, Luke V. Rasmussen, Firas H. Wehbe, Josh F. Peterson, Jamie R. Robinson, Ken Wiley, Casey Overby Taylor, and eMERGE Network EHRI Working Group
- Published
- 2018
- Full Text
- View/download PDF
3. Design and Implementation of a Structured Sequencing Report Format: A Multi-Stakeholder Perspective from eMERGE.
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Luke V. Rasmussen, Darren C. Ames, Samuel J. Aronson, Lawrence J. Babb, and Casey L. Overby
- Published
- 2017
4. Neptune: an environment for the delivery of genomic medicine
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Venner Eric, Victoria Yi, David Murdock, Sara E. Kalla, Tsung-Jung Wu, Aniko Sabo, Shoudong Li, Qingchang Meng, Xia Tian, Mullai Murugan, Michelle Cohen, Christie Kovar, Wei-Qi Wei, Wendy K. Chung, Chunhua Weng, Georgia L. Wiesner, Gail P. Jarvik, Donna Muzny, Richard A. Gibbs, Debra Abrams, Samuel E. Adunyah, Ladia Albertson-Junkans, Berta Almoguera, Darren C. Ames, Paul Appelbaum, Samuel Aronson, Sharon Aufox, Lawrence J. Babb, Adithya Balasubramanian, Hana Bangash, Melissa Basford, Lisa Bastarache, Samantha Baxter, Meckenzie Behr, Barbara Benoit, Elizabeth Bhoj, Suzette J. Bielinski, Sarah T. Bland, Carrie Blout, Kenneth Borthwick, Erwin P. Bottinger, Mark Bowser, Harrison Brand, Murray Brilliant, Wendy Brodeur, Pedro Caraballo, David Carrell, Andrew Carroll, Lisa Castillo, Victor Castro, Gauthami Chandanavelli, Theodore Chiang, Rex L. Chisholm, Kurt D. Christensen, Wendy Chung, Christopher G. Chute, Brittany City, Beth L. Cobb, John J. Connolly, Paul Crane, Katherine Crew, David R. Crosslin, Jyoti Dayal, Mariza De Andrade, Jessica De la Cruz, Josh C. Denny, Shawn Denson, Tim DeSmet, Ozan Dikilitas, Michael J. Dinsmore, Sheila Dodge, Phil Dunlea, Todd L. Edwards, Christine M. Eng, David Fasel, Alex Fedotov, Qiping Feng, Mark Fleharty, Andrea Foster, Robert Freimuth, Christopher Friedrich, Stephanie M. Fullerton, Birgit Funke, Stacey Gabriel, Vivian Gainer, Ali Gharavi, Andrew M. Glazer, Joseph T. Glessner, Jessica Goehringer, Adam S. Gordon, Chet Graham, Robert C. Green, Justin H. Gundelach, Heather S. Hain, Hakon Hakonarson, Maegan V. Harden, John Harley, Margaret Harr, Andrea Hartzler, M. Geoffrey Hayes, Scott Hebbring, Nora Henrikson, Andrew Hershey, Christin Hoell, Ingrid Holm, Kayla M. Howell, George Hripcsak, Jianhong Hu, Elizabeth Duffy Hynes, Joy C. Jayaseelan, Yunyun Jiang, Yoonjung Yoonie Joo, Sheethal Jose, Navya Shilpa Josyula, Anne E. Justice, Divya Kalra, Elizabeth W. Karlson, Brendan J. Keating, Melissa A. Kelly, Eimear E. Kenny, Dustin Key, Krzysztof Kiryluk, Terrie Kitchner, Barbara Klanderman, Eric Klee, David C. Kochan, Viktoriya Korchina, Leah Kottyan, Emily Kudalkar, Alanna Kulchak Rahm, Iftikhar J. Kullo, Philip Lammers, Eric B. Larson, Matthew S. Lebo, Magalie Leduc, Ming Ta (Michael) Lee, Niall J. Lennon, Kathleen A. Leppig, Nancy D. Leslie, Rongling Li, Wayne H. Liang, Chiao-Feng Lin, Jodell E. Linder, Noralane M. Lindor, Todd Lingren, James G. Linneman, Cong Liu, Wen Liu, Xiuping Liu, John Lynch, Hayley Lyon, Alyssa Macbeth, Harshad Mahadeshwar, Lisa Mahanta, Bradley Malin, Teri Manolio, Maddalena Marasa, Keith Marsolo, Michelle L. McGowan, Elizabeth McNally, Jim Meldrim, Frank Mentch, Hila Milo Rasouly, Jonathan Mosley, Shubhabrata Mukherjee, Thomas E. Mullen, Jesse Muniz, David R. Murdock, Shawn Murphy, Melanie F. Myers, Bahram Namjou, Yizhao Ni, Robert C. Onofrio, Aniwaa Owusu Obeng, Thomas N. Person, Josh F. Peterson, Lynn Petukhova, Cassandra J. Pisieczko, Siddharth Pratap, Cynthia A. Prows, Megan J. Puckelwartz, Ritika Raj, James D. Ralston, Arvind Ramaprasan, Andrea Ramirez, Luke Rasmussen, Laura Rasmussen-Torvik, Soumya Raychaudhuri, Heidi L. Rehm, Marylyn D. Ritchie, Catherine Rives, Beenish Riza, Dan M. Roden, Elisabeth A. Rosenthal, Avni Santani, Schaid Dan, Steven Scherer, Stuart Scott, Aaron Scrol, Soumitra Sengupta, Ning Shang, Himanshu Sharma, Richard R. Sharp, Rajbir Singh, Patrick M.A. Sleiman, Kara Slowik, Joshua C. Smith, Maureen E. Smith, Duane T. Smoot, Jordan W. Smoller, Sunghwan Sohn, Ian B. Stanaway, Justin Starren, Mary Stroud, Jessica Su, Casey Overby Taylor, Kasia Tolwinski, Sara L. Van Driest, Sean M. Vargas, Matthew Varugheese, David Veenstra, Eric Venner, Miguel Verbitsky, Gina Vicente, Michael Wagner, Kimberly Walker, Theresa Walunas, Liwen Wang, Qiaoyan Wang, Scott T. Weiss, Quinn S. Wells, Peter S. White, Ken L. Wiley, Janet L. Williams, Marc S. Williams, Michael W. Wilson, Leora Witkowski, Laura Allison Woods, Betty Woolf, Julia Wynn, Yaping Yang, Ge Zhang, Lan Zhang, and Hana Zouk
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Computer science ,business.industry ,Process (engineering) ,MEDLINE ,High-Throughput Nucleotide Sequencing ,Genomics ,Data science ,Article ,Personalization ,Variety (cybernetics) ,Workflow ,Neptune ,Pharmacogenomics ,Health care ,Electronic Health Records ,Humans ,business ,Software ,Genetics (clinical) - Abstract
Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .
- Published
- 2021
- Full Text
- View/download PDF
5. Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network
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Ian B. Stanaway, Dan M. Roden, Divya Kalra, Dustin Key, Debra J. Abrams, David Fasel, Victor Castro, Brad Malin, Berta Almoguera, Beenish Riza, Meckenzie A. Behr, Eric Venner, Christine M. Eng, Joy Jayaseelan, Scott J. Hebbring, Michelle L. McGowan, Steven E. Scherer, Theresa L. Walunas, Mark Bowser, James D. Ralston, Wei-Qi Wei, Liwen Wang, David R. Murdock, Wayne H. Liang, Julia Wynn, Nancy D. Leslie, Laura J. Rasmussen-Torvik, Ming Ta (Michael) Lee, Frank D. Mentch, Lan Zhang, Alanna Kulchak Rahm, Josh F. Peterson, Jodell E. Linder, Joshua C. Smith, Soumitra Sengupta, Brendan J. Keating, Gina Vicente, Andrew Carroll, Nora B. Henrikson, Anne E. Justice, Heather S. Hain, Wen Liu, Andrea H. Ramirez, Matthew S. Lebo, Hana Zouk, Georgia L. Wiesner, Andrea L. Hartzler, Cassandra J. Pisieczko, Catherine M. Rives, Jessica Goehringer, Maegan V. Harden, John Lynch, Chiao-Feng Lin, Peter White, Phil Dunlea, Shawn N. Murphy, Mullai Murugan, Harshad Mahadeshwar, Mark Fleharty, Andrea Foster, Arvind Ramaprasan, Christopher A. Friedrich, Justin H. Gundelach, Hayley Lyon, Niall J. Lennon, Eric W. Klee, David R. Crosslin, Ge Zhang, Rongling Li, Ozan Dikilitas, Xiuping Liu, Christin Hoell, Aniwaa Owusu Obeng, Katherine D. Crew, Lisa M. Castillo, Justin Starren, Jonathan D. Mosley, Carrie L. Blout, Himanshu Sharma, Elizabeth M. McNally, Sarah T. Bland, Megan J. Puckelwartz, Matthew Varugheese, Keith Marsolo, Betty Woolf, Sharon Aufox, Janet L. Williams, Kimberly Walker, Murray H. Brilliant, Birgit Funke, Laura Allison Woods, Marylyn D. Ritchie, Brittany City, Todd Lingren, Hila Milo Rasouly, Lawrence J. Babb, Alex Fedotov, Robert C. Onofrio, Margaret Harr, Suzette J. Bielinski, Michael W. Wilson, Shubhabrata Mukherjee, Robert R. Freimuth, Chet Graham, Todd L. Edwards, Quinn S. Wells, Marc S. Williams, Jordan W. Smoller, Wendy K. Chung, Avni Santani, Paul K. Crane, George Hripcsak, QiPing Feng, Ali G. Gharavi, Yizhao Ni, Iftikhar J. Kullo, Michael Wagner, Philip E. Lammers, Michael J. Dinsmore, Thomas N. Person, Victoria Yi, Samuel E. Adunyah, Tim DeSmet, Eric B. Larson, Elizabeth Hynes, David C. Kochan, Eimear E. Kenny, Magalie S. Leduc, Lisa Mahanta, David Carrell, Paul S. Appelbaum, Viktoriya Korchina, Beth L. Cobb, Lynn Petukhova, Jessica De la Cruz, Patrick M. A. Sleiman, Stuart A. Scott, Tsung-Jung Wu, Gail P. Jarvik, Erwin P. Bottinger, Ken Wiley, Josh C. Denny, Melissa A. Basford, Samuel J. Aronson, David L. Veenstra, Yaping Yang, Kayla Marie Howell, John J. Connolly, Jessica Su, Yoonjung Yoonie Joo, Miguel Verbitsky, Sean M. Vargas, Cong Liu, Barbara Benoit, Andrew Hershey, Richard A. Gibbs, Cynthia A. Prows, Hana Bangash, Wendy Brodeur, Gauthami Chandanavelli, Sara L. Van Driest, Kurt D. Christensen, Elizabeth J. Bhoj, Vivian S. Gainer, Adam S. Gordon, Robert C. Green, Hakon Hakonarson, Krzysztof Kiryluk, Elisabeth A. Rosenthal, Rajbir Singh, James G. Linneman, Harrison Brand, Theodore Chiang, Sheila Dodge, Ingrid A. Holm, M. Geoffrey Hayes, Yunyun Jiang, Ning Shang, Samantha Baxter, Noralane M. Lindor, Kathleen A. Leppig, Teri A. Manolio, Sara E. Kalla, Pedro J. Caraballo, Ritika Raj, Aaron Scrol, Jyoti G. Dayal, Richard R. Sharp, Christie Kovar, Soumya Raychaudhuri, Sunghwan Sohn, Emily Kudalkar, Maddalena Marasa, Stacey Gabriel, Dan Schaid, Ladia Albertson-Junkans, Rex L. Chisholm, Maureen E. Smith, Donna M. Muzny, Casey Overby Taylor, Jianhong Hu, Elizabeth W. Karlson, Lisa Bastarache, Darren C. Ames, Joseph T. Glessner, Leora Witkowski, Siddharth Pratap, Qiaoyan Wang, Melissa A. Kelly, Adithya Balasubramanian, Kara Slowik, Terrie Kitchner, Barbara J. Klanderman, Shawn Denson, Mary Stroud, Alyssa Macbeth, Melanie F. Myers, Jesse Muniz, Kasia Tolwinski, Scott T. Weiss, Chunhua Weng, Stephanie M. Fullerton, John B. Harley, Christopher G. Chute, Heidi L. Rehm, Sheethal Jose, Andrew M. Glazer, Navya Shilpa Josyula, Kenneth M. Borthwick, Thomas E. Mullen, Mariza de Andrade, Leah C. Kottyan, Luke V. Rasmussen, James Meldrim, and Bahram Namjou
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0301 basic medicine ,Standardization ,Test data generation ,business.industry ,Computer science ,Sequence Analysis, DNA ,030105 genetics & heredity ,Precision medicine ,Data science ,Clinical decision support system ,Biobank ,Article ,3. Good health ,Data sharing ,03 medical and health sciences ,030104 developmental biology ,Genetics ,Humans ,Genetic Testing ,Prospective Studies ,Sample collection ,Personalized medicine ,Precision Medicine ,business ,Genetics (clinical) - Abstract
The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.
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- 2019
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6. Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects
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Manisha Kher, Hyun Min Kang, Yossi Farjoun, Eric Banks, Allison A. Regier, Olga Krasheninina, Gonçalo R. Abecasis, Yeting Zhang, Tara C. Matise, Ira M. Hall, Daniel P. Howrigan, Jinchuan Xing, Will Salerno, Bo Juen Chen, Benjamin M. Neale, Adam C. English, David E. Larson, Heng Li, Michael C. Zody, and Darren C. Ames
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0301 basic medicine ,Computer science ,Science ,General Physics and Astronomy ,Computational biology ,Genome ,Article ,General Biochemistry, Genetics and Molecular Biology ,Statistical power ,Bottleneck ,DNA sequencing ,Structural variation ,03 medical and health sciences ,0302 clinical medicine ,Humans ,Nucleotide ,lcsh:Science ,Indel ,030304 developmental biology ,chemistry.chemical_classification ,Whole genome sequencing ,0303 health sciences ,Data processing ,Multidisciplinary ,Whole Genome Sequencing ,Genome, Human ,Scale (chemistry) ,Human Genetics ,General Chemistry ,Human genetics ,030104 developmental biology ,chemistry ,Genome Biology ,lcsh:Q ,030217 neurology & neurosurgery - Abstract
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., Sharing of whole genome sequencing (WGS) data improves study scale and power, but data from different groups are often incompatible. Here, US genome centers and NIH programs define WGS data processing standards and a flexible validation method, facilitating collaboration in human genetics research.
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- 2018
7. Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example
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Emily Beth Devine, Samuel J. Aronson, Andrea L. Hartzler, Keith Marsolo, Robert R. Freimuth, Casey Overby Taylor, Jamie R. Robinson, Pedro J. Caraballo, Luke V. Rasmussen, Darren C. Ames, Christopher G. Chute, Lawrence J. Babb, James D. Ralston, Shawn N. Murphy, Chunhua Weng, Iftikhar J. Kullo, Wayne H. Liang, Firas Wehbe, Ken Wiley, Richard A. Gibbs, Eric Venner, Marc S. Williams, John J. Connelly, and Josh F. Peterson
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0301 basic medicine ,Knowledge management ,Computer science ,Health Informatics ,Case Report ,Letter of transmittal ,Clinical decision support system ,03 medical and health sciences ,Computer Communication Networks ,Organizational boundaries ,Genomic medicine ,Electronic Health Records ,Humans ,Genetic Testing ,Point of care ,business.industry ,Genome, Human ,Information Dissemination ,Genomics ,Sequence Analysis, DNA ,United States ,Test (assessment) ,030104 developmental biology ,Work (electrical) ,business ,Healthcare providers - Abstract
The eMERGE Network is establishing methods for electronic transmittal of patient genetic test results from laboratories to healthcare providers across organizational boundaries. We surveyed the capabilities and needs of different network participants, established a common transfer format, and implemented transfer mechanisms based on this format. The interfaces we created are examples of the connectivity that must be instantiated before electronic genetic and genomic clinical decision support can be effectively built at the point of care. This work serves as a case example for both standards bodies and other organizations working to build the infrastructure required to provide better electronic clinical decision support for clinicians.
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- 2017
8. Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology
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Joshua C. Bis, Jennifer E. Huffman, Andrew D. Johnson, Colleen M. Sitlani, Susan R. Heckbert, Stephanie M. Gogarten, Andrew Carroll, Eric Boerwinkle, Braxton D. Mitchell, L. Adrienne Cupples, Alisa K. Manning, Cathy C. Laurie, James G. Wilson, Jeffrey R. O'Connell, Michael R. Brown, Xiaoming Liu, Stephen S. Rich, Matthew P. Conomos, Ramachandran S. Vasan, Joshua P. Lewis, Kenneth Rice, Stacey Gabriel, Alanna C. Morrison, Bruce M. Psaty, Nicholas L. Smith, Darren C. Ames, George J. Papanicolaou, Jerome I. Rotter, Cashell E. Jaquish, Namrata Gupta, William J Salerno, Achilleas N. Pitsillides, Jennifer A. Brody, and Richard A. Gibbs
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0301 basic medicine ,Big Data ,Big data ,Medical and Health Sciences ,Workflow ,0302 clinical medicine ,2.5 Research design and methodologies (aetiology) ,ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION ,Aetiology ,Lung ,education.field_of_study ,Molecular Epidemiology ,Genome ,Environmental resource management ,InformationSystems_DATABASEMANAGEMENT ,Biological Sciences ,Mobile Applications ,Networking and Information Technology R&D (NITRD) ,Regression Analysis ,TOPMed Hematology and Hemostasis Working Group ,Biotechnology ,education ,Population ,Information Dissemination ,Biology ,complex mixtures ,CHARGE Analysis and Bioinformatics Working Group ,Article ,03 medical and health sciences ,NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium ,Genetics ,Humans ,Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium ,Molecular epidemiology ,business.industry ,Extramural ,fungi ,Human Genome ,Fibrinogen ,equipment and supplies ,Data science ,ComputingMethodologies_PATTERNRECOGNITION ,030104 developmental biology ,Genetics, Population ,Good Health and Well Being ,Genetic epidemiology ,bacteria ,Generic health relevance ,business ,Commons ,030217 neurology & neurosurgery ,Software ,Developmental Biology - Abstract
The exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations.
- Published
- 2017
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