Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Daniel Mas-Montserrat"'
Autor:
Sonia Moreno-Grau, Manvi Vernekar, Arturo Lopez-Pineda, Daniel Mas-Montserrat, Míriam Barrabés, Consuelo D. Quinto-Cortés, Babak Moatamed, Ming Ta Michael Lee, Zhenning Yu, Kensuke Numakura, Yuta Matsuda, Jeffrey D. Wall, Alexander G. Ioannidis, Nicholas Katsanis, Tomohiro Takano, Carlos D. Bustamante
Publikováno v:
Human Genomics, Vol 18, Iss 1, Pp 1-12 (2024)
Abstract Background Polygenic risk scores (PRS) derived from European individuals have reduced portability across global populations, limiting their clinical implementation at worldwide scale. Here, we investigate the performance of a wide range of P
Externí odkaz:
https://doaj.org/article/35867bdc28c94826baeb727a7d8ffbc0
Autor:
Victoria N. Parikh, Alexander G. Ioannidis, David Jimenez-Morales, John E. Gorzynski, Hannah N. De Jong, Xiran Liu, Jonasel Roque, Victoria P. Cepeda-Espinoza, Kazutoyo Osoegawa, Chris Hughes, Shirley C. Sutton, Nathan Youlton, Ruchi Joshi, David Amar, Yosuke Tanigawa, Douglas Russo, Justin Wong, Jessie T. Lauzon, Jacob Edelson, Daniel Mas Montserrat, Yongchan Kwon, Simone Rubinacci, Olivier Delaneau, Lorenzo Cappello, Jaehee Kim, Massa J. Shoura, Archana N. Raja, Nathaniel Watson, Nathan Hammond, Elizabeth Spiteri, Kalyan C. Mallempati, Gonzalo Montero-Martín, Jeffrey Christle, Jennifer Kim, Anna Kirillova, Kinya Seo, Yong Huang, Chunli Zhao, Sonia Moreno-Grau, Steven G. Hershman, Karen P. Dalton, Jimmy Zhen, Jack Kamm, Karan D. Bhatt, Alina Isakova, Maurizio Morri, Thanmayi Ranganath, Catherine A. Blish, Angela J. Rogers, Kari Nadeau, Samuel Yang, Andra Blomkalns, Ruth O’Hara, Norma F. Neff, Christopher DeBoever, Sándor Szalma, Matthew T. Wheeler, Christian M. Gates, Kyle Farh, Gary P. Schroth, Phil Febbo, Francis deSouza, Omar E. Cornejo, Marcelo Fernandez-Vina, Amy Kistler, Julia A. Palacios, Benjamin A. Pinsky, Carlos D. Bustamante, Manuel A. Rivas, Euan A. Ashley
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-10 (2022)
There is a genetic component to the risk of severe COVID-19, but the genetic effects are difficult to separate from social constructs that covary with genetic ancestry. To address this, the authors identify determinants of COVID-19 severity using adm
Externí odkaz:
https://doaj.org/article/10002eca5587461185e42393a7dc16a5
Autor:
Julia Gimbernat-Mayol, Albert Dominguez Mantes, Carlos D Bustamante, Daniel Mas Montserrat, Alexander G Ioannidis
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 8, p e1010301 (2022)
The estimation of genetic clusters using genomic data has application from genome-wide association studies (GWAS) to demographic history to polygenic risk scores (PRS) and is expected to play an important role in the analyses of increasingly diverse,
Externí odkaz:
https://doaj.org/article/6adbe247b18441bc83db8195ac5b117f
Publikováno v:
Bioinformatics. 38:ii27-ii33
Availability and implementation: We provide an open source implementation and links to publicly available data at github.com/AI-sandbox/SALAI-Net. Data is publicly available as follows: https://www.internationalgenome.org (1000 Genomes), https://www.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9b51cfe22824fdab77161e515342812
https://doi.org/10.1093/bioinformatics/btac464
https://doi.org/10.1093/bioinformatics/btac464
Autor:
Emily R. Bartusiak, Míriam Barrabés, Aigerim Rymbekova, Julia Gimbernat-Mayol, Cayetana López, Lorenzo Barberis, Daniel Mas Montserrat, Xavier Giró-i-Nieto, Alexander G. Ioannidis
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2022
We analyze dog genotypes (i.e., positions of dog DNA sequences that often vary between different dogs) in order to predict the corresponding phenotypes (i.e., unique observed characteristics). More specifically, given chromosome data from a dog, we a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b070ec9b49c12eae76ed0ada2d327f6
https://pubmed.ncbi.nlm.nih.gov/36085664
https://pubmed.ncbi.nlm.nih.gov/36085664
The production of population-level trees using the genomic data of individuals is a fundamental task in the field of population genetics. Typically, these trees are produced using methods like hierarchical clustering, neighbor joining, or maximum lik
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f044510844da11f1c29092e9a9b032f
https://doi.org/10.1101/2022.03.28.484797
https://doi.org/10.1101/2022.03.28.484797
Autor:
Maria Perera, Daniel Mas Montserrat, Míriam Barrabés, Margarita Geleta, Xavier Giró-i-Nieto, Alexander G. Ioannidis
The generation of synthetic genomic sequences using neural networks has potential to ameliorate privacy and data sharing concerns and to mitigate potential bias within datasets due to under-representation of some population groups. However, there is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7556d57918cbf458d692e17e72380211
https://hdl.handle.net/2117/387315
https://hdl.handle.net/2117/387315
The estimation of genetic clusters using genomic data has application from genome-wide association studies (GWAS) to demographic history to polygenic risk scores (PRS) and is expected to play an important role in the analyses of increasingly diverse,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce92c3edb1174ae4327dcc14f9928512
https://doi.org/10.1101/2021.11.28.470296
https://doi.org/10.1101/2021.11.28.470296
Autor:
Helgi Hilmarsson, Alexander G. Ioannidis, Arvind Kumar, Richa Rastogi, Daniel Mas Montserrat, Carlos Bustamante
As genome-wide association studies and genetic risk prediction models are extended to globally diverse and admixed cohorts, ancestry deconvolution has become an increasingly important tool. Also known as local ancestry inference (LAI), this technique
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73c1a107ee4bba4dd8e2b2884c9fe90a
https://doi.org/10.1101/2021.09.19.460980
https://doi.org/10.1101/2021.09.19.460980
Autor:
Victoria N. Parikh, Alexander G. Ioannidis, David Jimenez-Morales, John E. Gorzynski, Hannah N. De Jong, Xiran Liu, Jonasel Roque, Victoria P. Cepeda-Espinoza, Kazutoyo Osoegawa, Chris Hughes, Shirley C. Sutton, Nathan Youlton, Ruchi Joshi, David Amar, Yosuke Tanigawa, Douglas Russo, Justin Wong, Jessie T. Lauzon, Jacob Edelson, Daniel Mas Montserrat, Yongchan Kwon, Simone Rubinacci, Olivier Delaneau, Lorenzo Cappello, Jaehee Kim, Massa J. Shoura, Archana N. Raja, Nathaniel Watson, Nathan Hammond, Elizabeth Spiteri, Kalyan C. Mallempati, Gonzalo Montero-Martín, Jeffrey Christle, Jennifer Kim, Anna Kirillova, Kinya Seo, Yong Huang, Chunli Zhao, Sonia Moreno-Grau, Steven G. Hershman, Karen P. Dalton, Jimmy Zhen, Jack Kamm, Karan D. Bhatt, Alina Isakova, Maurizio Morri, Thanmayi Ranganath, Catherine A. Blish, Angela J. Rogers, Kari Nadeau, Samuel Yang, Andra Blomkalns, Ruth O’Hara, Norma F. Neff, Christopher DeBoever, Sándor Szalma, Matthew T. Wheeler, Christian M. Gates, Kyle Farh, Gary P. Schroth, Phil Febbo, Francis deSouza, Omar E. Cornejo, Marcelo Fernandez-Vina, Amy Kistler, Julia A. Palacios, Benjamin A. Pinsky, Carlos D. Bustamante, Manuel A. Rivas, Euan A. Ashley
Publikováno v:
Nature communications, vol 13, iss 1
The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f118aae9b209086b4082f16691dd4607
https://pubmed.ncbi.nlm.nih.gov/36042219
https://pubmed.ncbi.nlm.nih.gov/36042219