Search

Your search keyword '"Nicole Deflaux"' showing total 8 results
Start Over Author "Nicole Deflaux"
8 results on '"Nicole Deflaux"'

1. Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis

Author

Nicole Deflaux, Margaret Sunitha Selvaraj, Henry Robert Condon, Kelsey Mayo, Sara Haidermota, Melissa A. Basford, Chris Lunt, Anthony A. Philippakis, Dan M. Roden, Joshua C. Denny, Anjene Musick, Rory Collins, Naomi Allen, Mark Effingham, David Glazer, Pradeep Natarajan, and Alexander G. Bick

Subjects
Science
Abstract

Abstract Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an external study shows strong correlation of known loci with lipid levels (R2 ~ 83–97%). Importantly, 90 variants meet the significance threshold only in the meta-analysis and 64 variants are significant only in pooled analysis, with approximately 20% of variants in each of those groups being most prevalent in non-European, non-Asian ancestry individuals. These findings have important implications, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.

Published
2023
Full Text
View/download PDF

2. The All of Us Research Program: Data quality, utility, and diversity.

Author

Andrea H. Ramirez, Lina M. Sulieman, David J. Schlueter, Alese E. Halvorson, Jun Qian, Francis Ratsimbazafy, Roxana Loperena-Cortes, Kelsey R. Mayo, Melissa A. Basford, Nicole Deflaux, Karthik Muthuraman, Karthik Natarajan, Abel N. Kho, Hua Xu 0001, Consuelo H. Wilkins, Hoda Anton-Culver, Eric Boerwinkle, Mine Cicek, Cheryl R. Clark, Elizabeth Cohn, Lucila Ohno-Machado, Sheri D. Schully, Brian K. Ahmedani, Maria Argos, Robert M. Cronin, Christopher J. O'Donnell, Mona Fouad, David B. Goldstein, Philip Greenland, Scott J. Hebbring, Elizabeth W. Karlson, Parinda Khatri, Bruce Korf, Jordan W. Smoller, Stephen Sodeke, John Wilbanks, Justin Hentges, Stephen Mockrin, Christopher Lunt, Stephanie A. Devaney, Kelly Gebo, Joshua C. Denny, Robert J. Carroll, David Glazer, Paul A. Harris, George Hripcsak, Anthony A. Philippakis, and Dan M. Roden

Published
2022
Full Text
View/download PDF

4. JUMP Cell Painting dataset: morphological impact of 136,000 chemical and genetic perturbations

Author

Srinivas Niranj Chandrasekaran, Jeanelle Ackerman, Eric Alix, D. Michael Ando, John Arevalo, Melissa Bennion, Nicolas Boisseau, Adriana Borowa, Justin D. Boyd, Laurent Brino, Patrick J. Byrne, Hugo Ceulemans, Carolyn Ch’ng, Beth A. Cimini, Djork-Arne Clevert, Nicole Deflaux, John G Doench, Thierry Dorval, Regis Doyonnas, Vincenza Dragone, Ola Engkvist, Patrick W. Faloon, Briana Fritchman, Florian Fuchs, Sakshi Garg, Tamara J. Gilbert, David Glazer, David Gnutt, Amy Goodale, Jeremy Grignard, Judith Guenther, Yu Han, Zahra Hanifehlou, Santosh Hariharan, Desiree Hernandez, Shane R Horman, Gisela Hormel, Michael Huntley, Ilknur Icke, Makiyo Iida, Christina B. Jacob, Steffen Jaensch, Jawahar Khetan, Maria Kost-Alimova, Tomasz Krawiec, Daniel Kuhn, Charles-Hugues Lardeau, Amanda Lembke, Francis Lin, Kevin D. Little, Kenneth R. Lofstrom, Sofia Lotfi, David J. Logan, Yi Luo, Franck Madoux, Paula A. Marin Zapata, Brittany A. Marion, Glynn Martin, Nicola Jane McCarthy, Lewis Mervin, Lisa Miller, Haseeb Mohamed, Tiziana Monteverde, Elizabeth Mouchet, Barbara Nicke, Arnaud Ogier, Anne-Laure Ong, Marc Osterland, Magdalena Otrocka, Pieter J. Peeters, James Pilling, Stefan Prechtl, Chen Qian, Krzysztof Rataj, David E Root, Sylvie K. Sakata, Simon Scrace, Hajime Shimizu, David Simon, Peter Sommer, Craig Spruiell, Iffat Sumia, Susanne E Swalley, Hiroki Terauchi, Amandine Thibaudeau, Amy Unruh, Jelle Van de Waeter, Michiel Van Dyck, Carlo van Staden, Michał Warchoł, Erin Weisbart, Amélie Weiss, Nicolas Wiest-Daessle, Guy Williams, Shan Yu, Bolek Zapiec, Marek Żyła, Shantanu Singh, and Anne E. Carpenter

Abstract

Image-based profiling has emerged as a powerful technology for various steps in basic biological and pharmaceutical discovery, but the community has lacked a large, public reference set of data from chemical and genetic perturbations. Here we present data generated by the Joint Undertaking for Morphological Profiling (JUMP)-Cell Painting Consortium, a collaboration between 10 pharmaceutical companies, six supporting technology companies, and two non-profit partners. When completed, the dataset will contain images and profiles from the Cell Painting assay for over 116,750 unique compounds, over-expression of 12,602 genes, and knockout of 7,975 genes using CRISPR-Cas9, all in human osteosarcoma cells (U2OS). The dataset is estimated to be 115 TB in size and capturing 1.6 billion cells and their single-cell profiles. File quality control and upload is underway and will be completed over the coming months at the Cell Painting Gallery:https://registry.opendata.aws/cellpainting-gallery. A portal to visualize a subset of the data is available athttps://phenaid.ardigen.com/jumpcpexplorer/.

Published
2023
Full Text
View/download PDF

5. Cloud gazing: demonstrating paths for unlocking the value of cloud genomics through cross-cohort analysis

Author

Nicole Deflaux, Margaret Sunitha Selvaraj, Henry Robert Condon, Kelsey Mayo, Sara Haidermota, Melissa A. Basford, Chris Lunt, Anthony A. Philippakis, Dan M. Roden, Josh C. Denny, Anjene Musick, Rory Collins, Naomi Allen, Mark Effingham, David Glazer, Pradeep Natarajan, and Alexander G. Bick

Abstract

The rapid growth of genomic data has led to a new research paradigm where data are stored centrally in Trusted Research Environments (TREs) such as theAll of UsResearcher Workbench (AoU RW) and the UK Biobank Research Analysis Platform (RAP). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conducted a Genome-Wide Association Study (GWAS) of standard lipid measures on the UKB RAP and AoU RW using two approaches: meta-analysis and pooled analysis. We curated lipid measurements for 37,754All of Usparticipants with whole genome sequence (WGS) data and 190,982 UK Biobank participants with whole exome sequence (WES) data. For the meta-analysis, we performed a GWAS of each cohort in their respective platform and meta-analyzed the results. We separately performed a pooled GWAS on both datasets combined. We identified 490 and 464 significant variants in meta-analysis and pooled analysis, respectively. Comparison of full summary data from both meta-analysis and pooled analysis with an external study showed strong correlation of known loci with lipid levels (R2∼83-97%). Importantly, 90 variants met the significance threshold only in the meta-analysis and 64 variants were significant only in pooled analysis. These method-specific differences may be explained by differences in cohort size, ancestry, and phenotype distributions inAll of Usand UK Biobank. We noted approximately 20% of variants significant in only the pooled analysis or significant in only the meta-analysis were most prevalent in non-European, non-Asian ancestry individuals. Pooled analyses included more variants than meta-analyses. Pooled analysis required about half as many computational steps as meta-analysis. These findings have important implications for both platform implementations and researchers undertaking large-scale cross-cohort analyses, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.

Published
2022
Full Text
View/download PDF

6. Genomic architecture of Autism Spectrum Disorder from comprehensive whole-genome sequence annotation

Author

Brett Trost, Bhooma Thiruvahindrapuram, Ada J.S. Chan, Worrawat Engchuan, Edward J. Higginbotham, Jennifer L. Howe, Livia O. Loureiro, Miriam S. Reuter, Delnaz Roshandel, Joe Whitney, Mehdi Zarrei, Matthew Bookman, Cherith Somerville, Rulan Shaath, Mona Abdi, Elbay Aliyev, Rohan V. Patel, Thomas Nalpathamkalam, Giovanna Pellecchia, Omar Hamdan, Gaganjot Kaur, Zhuozhi Wang, Jeffrey R. MacDonald, John Wei, Wilson W.L. Sung, Sylvia Lamoureux, Ny Hoang, Thanuja Selvanayagam, Nicole Deflaux, Melissa Geng, Siavash Ghaffari, John Bates, Edwin J. Young, Qiliang Ding, Carole Shum, Lia D’abate, Clarissa A. Bradley, Annabel Rutherford, Vernie Aguda, Beverly Apresto, Nan Chen, Sachin Desai, Xiaoyan Du, Matthew L.Y. Fong, Sanjeev Pullenayegum, Kozue Samler, Ting Wang, Karen Ho, Tara Paton, Sergio L. Pereira, Jo-Anne Herbrick, Richard F. Wintle, Jonathan Fuerth, Juti Noppornpitak, Heather Ward, Patrick Magee, Ayman Al Baz, Usanthan Kajendirarajah, Sharvari Kapadia, Jim Vlasblom, Monica Valluri, Joseph Green, Vicki Seifer, Morgan Quirbach, Olivia Rennie, Elizabeth Kelley, Nina Masjedi, Catherine Lord, Michael J. Szego, Ma’n H. Zawati, Michael Lang, Lisa J. Strug, Christian R. Marshall, Gregory Costain, Kristina Calli, Alana Iaboni, Afiqah Yusuf, Patricia Ambrozewicz, Louise Gallagher, David G. Amaral, Jessica Brian, Mayada Elsabbagh, Stelios Georgiades, Daniel S. Messinger, Sally Ozonoff, Jonathan Sebat, Calvin Sjaarda, Isabel M. Smith, Peter Szatmari, Lonnie Zwaigenbaum, Azadeh Kushki, Thomas W. Frazier, Jacob A.S. Vorstman, Khalid A. Fakhro, Bridget A. Fernandez, M.E. Suzanne Lewis, Rosanna Weksberg, Marc Fiume, Ryan K.C. Yuen, Evdokia Anagnostou, Neal Sondheimer, David Glazer, Dean M. Hartley, and Stephen W. Scherer

Abstract

Fully understanding the genetic factors involved in Autism Spectrum Disorder (ASD) requires whole-genome sequencing (WGS), which theoretically allows the detection of all types of genetic variants. With the aim of generating an unprecedented resource for resolving the genomic architecture underlying ASD, we analyzed genome sequences and phenotypic data from 5,100 individuals with ASD and 6,212 additional parents and siblings (total n=11,312) in the Autism Speaks MSSNG Project, as well as additional individuals from other WGS cohorts. WGS data and autism phenotyping were based on high-quality short-read sequencing (>30x coverage) and clinically accepted diagnostic measures for ASD, respectively. For initial discovery of ASD-associated genes, we used exonic sequence-level variants from MSSNG as well as whole-exome sequencing-based ASD data from SPARK and the Autism Sequencing Consortium (>18,000 trios plus additional cases and controls), identifying 135 ASD-associated protein-coding genes with false discovery rate SCN2A and a nuclear mitochondrial insertion impacting SYNGAP1. Polygenic risk scores did not differ between children with ASD in multiplex families versus simplex, and rare, damaging recessive events were significantly depleted in multiplex families, collectively suggesting that rare, dominant variation plays a predominant role in multiplex ASD. Our study provides a guidebook for exploring genotype-phenotype correlations in the 15-20% of ASD families who carry ASD-associated rare variants, as well as an entry point to the larger and more diverse studies that will be required to dissect the etiology in the >80% of the ASD population that remains idiopathic. All data resulting from this study are available to the medical genomics research community in an open but protected manner.

Published
2022
Full Text
View/download PDF

7. The

Author

Andrea H, Ramirez, Lina, Sulieman, David J, Schlueter, Alese, Halvorson, Jun, Qian, Francis, Ratsimbazafy, Roxana, Loperena, Kelsey, Mayo, Melissa, Basford, Nicole, Deflaux, Karthik N, Muthuraman, Karthik, Natarajan, Abel, Kho, Hua, Xu, Consuelo, Wilkins, Hoda, Anton-Culver, Eric, Boerwinkle, Mine, Cicek, Cheryl R, Clark, Elizabeth, Cohn, Lucila, Ohno-Machado, Sheri D, Schully, Brian K, Ahmedani, Maria, Argos, Robert M, Cronin, Christopher, O'Donnell, Mona, Fouad, David B, Goldstein, Philip, Greenland, Scott J, Hebbring, Elizabeth W, Karlson, Parinda, Khatri, Bruce, Korf, Jordan W, Smoller, Stephen, Sodeke, John, Wilbanks, Justin, Hentges, Stephen, Mockrin, Christopher, Lunt, Stephanie A, Devaney, Kelly, Gebo, Joshua C, Denny, Robert J, Carroll, David, Glazer, Paul A, Harris, George, Hripcsak, Anthony, Philippakis, Dan M, Roden, and Michael E, Zwick

Abstract

The

Published
2022

8. Genomic architecture of autism from comprehensive whole-genome sequence annotation

Author

Brett Trost, Bhooma Thiruvahindrapuram, Ada J.S. Chan, Worrawat Engchuan, Edward J. Higginbotham, Jennifer L. Howe, Livia O. Loureiro, Miriam S. Reuter, Delnaz Roshandel, Joe Whitney, Mehdi Zarrei, Matthew Bookman, Cherith Somerville, Rulan Shaath, Mona Abdi, Elbay Aliyev, Rohan V. Patel, Thomas Nalpathamkalam, Giovanna Pellecchia, Omar Hamdan, Gaganjot Kaur, Zhuozhi Wang, Jeffrey R. MacDonald, John Wei, Wilson W.L. Sung, Sylvia Lamoureux, Ny Hoang, Thanuja Selvanayagam, Nicole Deflaux, Melissa Geng, Siavash Ghaffari, John Bates, Edwin J. Young, Qiliang Ding, Carole Shum, Lia D'Abate, Clarrisa A. Bradley, Annabel Rutherford, Vernie Aguda, Beverly Apresto, Nan Chen, Sachin Desai, Xiaoyan Du, Matthew L.Y. Fong, Sanjeev Pullenayegum, Kozue Samler, Ting Wang, Karen Ho, Tara Paton, Sergio L. Pereira, Jo-Anne Herbrick, Richard F. Wintle, Jonathan Fuerth, Juti Noppornpitak, Heather Ward, Patrick Magee, Ayman Al Baz, Usanthan Kajendirarajah, Sharvari Kapadia, Jim Vlasblom, Monica Valluri, Joseph Green, Vicki Seifer, Morgan Quirbach, Olivia Rennie, Elizabeth Kelley, Nina Masjedi, Catherine Lord, Michael J. Szego, Ma'n H. Zawati, Michael Lang, Lisa J. Strug, Christian R. Marshall, Gregory Costain, Kristina Calli, Alana Iaboni, Afiqah Yusuf, Patricia Ambrozewicz, Louise Gallagher, David G. Amaral, Jessica Brian, Mayada Elsabbagh, Stelios Georgiades, Daniel S. Messinger, Sally Ozonoff, Jonathan Sebat, Calvin Sjaarda, Isabel M. Smith, Peter Szatmari, Lonnie Zwaigenbaum, Azadeh Kushki, Thomas W. Frazier, Jacob A.S. Vorstman, Khalid A. Fakhro, Bridget A. Fernandez, M.E. Suzanne Lewis, Rosanna Weksberg, Marc Fiume, Ryan K.C. Yuen, Evdokia Anagnostou, Neal Sondheimer, David Glazer, Dean M. Hartley, and Stephen W. Scherer

Subjects
DNA Copy Number Variations, Autism Spectrum Disorder, Humans, Genetic Predisposition to Disease, Genomics, Autistic Disorder, General Biochemistry, Genetics and Molecular Biology
Abstract

Fully understanding autism spectrum disorder (ASD) genetics requires whole-genome sequencing (WGS). We present the latest release of the Autism Speaks MSSNG resource, which includes WGS data from 5,100 individuals with ASD and 6,212 non-ASD parents and siblings (total n = 11,312). Examining a wide variety of genetic variants in MSSNG and the Simons Simplex Collection (SSC; n = 9,205), we identified ASD-associated rare variants in 718/5,100 individuals with ASD from MSSNG (14.1%) and 350/2,419 from SSC (14.5%). Considering genomic architecture, 52% were nuclear sequence-level variants, 46% were nuclear structural variants (including copy-number variants, inversions, large insertions, uniparental isodisomies, and tandem repeat expansions), and 2% were mitochondrial variants. Our study provides a guidebook for exploring genotype-phenotype correlations in families who carry ASD-associated rare variants and serves as an entry point to the expanded studies required to dissect the etiology in the ∼85% of the ASD population that remain idiopathic.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results