Добірка наукової літератури з теми "Genome-Wide polygenic score"
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Статті в журналах з теми "Genome-Wide polygenic score"
Forrest, Iain S., Kumardeep Chaudhary, Ishan Paranjpe, Ha My T. Vy, Carla Marquez-Luna, Ghislain Rocheleau, Aparna Saha, et al. "Genome-wide polygenic risk score for retinopathy of type 2 diabetes." Human Molecular Genetics 30, no. 10 (March 10, 2021): 952–60. http://dx.doi.org/10.1093/hmg/ddab067.
Повний текст джерелаDauber, Andrew, Yan Meng, Laura Audi, Sailaja Vedantam, Benjamin Weaver, Antonio Carrascosa, Kerstin Albertsson-Wikland, et al. "A Genome-Wide Pharmacogenetic Study of Growth Hormone Responsiveness." Journal of Clinical Endocrinology & Metabolism 105, no. 10 (July 11, 2020): 3203–14. http://dx.doi.org/10.1210/clinem/dgaa443.
Повний текст джерелаThomas, Minta, Lori C. Sakoda, Michael Hoffmeister, Elisabeth A. Rosenthal, Jeffrey K. Lee, Franzel J. B. van Duijnhoven, Elizabeth A. Platz, et al. "Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk." American Journal of Human Genetics 107, no. 3 (September 2020): 432–44. http://dx.doi.org/10.1016/j.ajhg.2020.07.006.
Повний текст джерелаChoi, Shing Wan, Judit García-González, Yunfeng Ruan, Hei Man Wu, Christian Porras, Jessica Johnson, Clive J. Hoggart, and Paul F. O’Reilly. "PRSet: Pathway-based polygenic risk score analyses and software." PLOS Genetics 19, no. 2 (February 7, 2023): e1010624. http://dx.doi.org/10.1371/journal.pgen.1010624.
Повний текст джерелаCurtis, David. "Clinical relevance of genome‐wide polygenic score may be less than claimed." Annals of Human Genetics 83, no. 4 (March 25, 2019): 274–77. http://dx.doi.org/10.1111/ahg.12302.
Повний текст джерелаLang, M., T. Leménager, F. Streit, M. Fauth-Bühler, J. Frank, D. Juraeva, S. H. Witt, et al. "Genome-wide association study of pathological gambling." European Psychiatry 36 (August 2016): 38–46. http://dx.doi.org/10.1016/j.eurpsy.2016.04.001.
Повний текст джерелаPain, Oliver, Alexandra C. Gillett, Jehannine C. Austin, Lasse Folkersen, and Cathryn M. Lewis. "A tool for translating polygenic scores onto the absolute scale using summary statistics." European Journal of Human Genetics 30, no. 3 (January 4, 2022): 339–48. http://dx.doi.org/10.1038/s41431-021-01028-z.
Повний текст джерелаParanjpe, Ishan, Noah Tsao, Renae Judy, Manish Paranjpe, Kumardeep Chaudhary, Derek Klarin, Iain Forrest, et al. "Derivation and validation of genome-wide polygenic score for urinary tract stone diagnosis." Kidney International 98, no. 5 (November 2020): 1323–30. http://dx.doi.org/10.1016/j.kint.2020.04.055.
Повний текст джерелаSexton, Corinne E., Mark T. W. Ebbert, Ryan H. Miller, Meganne Ferrel, Jo Ann T. Tschanz, Christopher D. Corcoran, Alzheimer’s Disease Neuroimaging Initiative, Perry G. Ridge, and John S. K. Kauwe. "Common DNA Variants Accurately Rank an Individual of Extreme Height." International Journal of Genomics 2018 (September 4, 2018): 1–7. http://dx.doi.org/10.1155/2018/5121540.
Повний текст джерелаBelsky, Daniel W., Benjamin W. Domingue, Robbee Wedow, Louise Arseneault, Jason D. Boardman, Avshalom Caspi, Dalton Conley, et al. "Genetic analysis of social-class mobility in five longitudinal studies." Proceedings of the National Academy of Sciences 115, no. 31 (July 9, 2018): E7275—E7284. http://dx.doi.org/10.1073/pnas.1801238115.
Повний текст джерелаДисертації з теми "Genome-Wide polygenic score"
Kawaguchi, Takahisa. "Risk estimation model for nonalcoholic fatty liver disease in the Japanese using multiple genetic markers." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263348.
Повний текст джерелаPrivé, Florian. "Genetic risk score based on statistical learning Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr Efficient implementation of penalized regression for genetic risk prediction Making the most of Clumping and Thresholding for polygenic scores." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAS024.
Повний текст джерелаGenotyping is becoming cheaper, making genotype data available for millions of indi-viduals. Moreover, imputation enables to get genotype information at millions of locicapturing most of the genetic variation in the human genome. Given such large data andthe fact that many traits and diseases are heritable (e.g. 80% of the variation of heightin the population can be explained by genetics), it is envisioned that predictive modelsbased on genetic information will be part of a personalized medicine.In my thesis work, I focused on improving predictive ability of polygenic models.Because prediction modeling is part of a larger statistical analysis of datasets, I de-veloped tools to allow flexible exploratory analyses of large datasets, which consist intwo R/C++ packages described in the first part of my thesis. Then, I developed someefficient implementation of penalized regression to build polygenic models based onhundreds of thousands of genotyped individuals. Finally, I improved the “clumping andthresholding” method, which is the most widely used polygenic method and is based onsummary statistics that are widely available as compared to individual-level data.Overall, I applied many concepts of statistical learning to genetic data. I used ex-treme gradient boosting for imputing genotyped variants, feature engineering to cap-ture recessive and dominant effects in penalized regression, and parameter tuning andstacked regressions to improve polygenic prediction. Statistical learning is not widelyused in human genetics and my thesis is an attempt to change that
Shen, Hanyang, Bizu Gelaye, Hailiang Huang, Marta B. Rondon, Sixto Sanchez, and Laramie E. Duncan. "Polygenic prediction and GWAS of depression, PTSD, and suicidal ideation/self-harm in a Peruvian cohort." Springer Nature, 2020. http://hdl.handle.net/10757/652459.
Повний текст джерелаNational Institutes of Health
Revisión por pares
Meijsen, Joeri Jeroen. "Combining genome-wide association studies, polygenic risk scores and SNP-SNP interactions to investigate the genomic architecture of human complex diseases : more than the sum of its parts." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33094.
Повний текст джерелаLind, Mackenzie J. "Sleep disturbances and depression: the role of genes and trauma." VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/4858.
Повний текст джерелаHuang, Xiufeng. "Immunogenetics of acute anterior uveitis and comparison to ankylosing spondylitis." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/213839/1/Xiufeng_Huang_Thesis.pdf.
Повний текст джерелаCharmet, Romain. "Étude des interactions entre la fonction rénale, la thrombose artérielle et la thrombose veineuse par une approche génétique Novel risk genes identified in a genome‑wide association study for coronary artery disease in patients with type 1 diabetes Association of impaired renal function with venous thrombosis: A genetic risk score approach." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS392.
Повний текст джерелаThis thesis deals with the study of genetic factors of coronary artery diseases as complications of type I diabetes, genetics factors of venous thrombosis and the interactions between these genetic factors and renal function. This work aims to add new pieces of knowledge concerning the role of renal function in the development of cardiovascular diseases. From a GWAS approach I aim to identify genetic markers associated with coronary artery disease within a group of type I diabetic patients a study the effect of the interaction between these markers and diabetic nephropathy. Then, I will study the link between renal function and venous thrombosis using a polygenetic risk score composed from genetic markers of renal function. This work highlighted new candidate genes associated with coronary artery disease among type I diabetic patients that are involved in kidney development and renal function. The association between the polygenetic risk score and renal function strengthened the hypothesis of renal function as a risk factor for venous thrombosis. The obtained results must be confirmed but they globally demonstrate that renal function plays a role in the development of cardiovascular diseases
Shih, Yu-Hsuan, and 施又瑄. "A Genome-wide Association Study of Neurocognitive Impairments in Schizophrenia: Polygenic Score Approach." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/70148708696391474501.
Повний текст джерела國立臺灣大學
流行病學與預防醫學研究所
102
Schizophrenia is considered to be genetically and phenotypically heterogeneous. The high heritability of neurocognitive impairments found in patients with schizophrenia suggests that these impairments may serve as an endophenotype resulting from a set of underlying genes in a mode of polygenic effects. In this study, a total of 165 schizophrenia patients were selected and these subjects were subjected to genotyping for 642,832 single nucleotide polymorphisms (SNPs). After quality control, 564,110 SNPs were left. We then performed principal component analysis (PCA) on 14 indices of the Continuous Performance Test (CPT) and the Wisconsin Card Sorting Test (WCST). Two orthogonal principal components (PC1 and PC2) identified with PCA explained 36.11% and 18.30% of the total variance, respectively. Then the two PCs were investigated for association with SNPs. Because of small sample size in this study, however, we were unable to detect SNPs associated with neurocognitive performance in schizophrenia with genome-wide significance. For exploring the polygenic effect, polygenic score analysis was conducted on 240,579 LD-based pruning SNPs (r2 > 0.5), which were imputed using MaCH and MiniMac. The sample was first randomly divided into a learning set (n = 83) and a test set (n = 82). Then the effect size (β) for the results of association test in the learning set was used to develop a linear model to generate scores in the test set. The sustained attention demonstrated a significant association (p = 0.03) with the PC1 polygenic score at a threshold of p = 0.0001 (25 markers), For the executive function, when polygenic scores in the test set was calculated based on the results of the best 0.1% of SNPs (219 markers) in the association study of learning set.
Книги з теми "Genome-Wide polygenic score"
Kan, Carol, and Ma-Li Wong. Genetics. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198789284.003.0004.
Повний текст джерелаLangley, Kate. ADHD genetics. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198739258.003.0003.
Повний текст джерелаЧастини книг з теми "Genome-Wide polygenic score"
Nurnberger, John I. "General genetics of bipolar disorder." In The Bipolar Brain, 200–222. Oxford University Press, 2022. http://dx.doi.org/10.1093/med/9780197574522.003.0011.
Повний текст джерелаHalldorsdottir, Thorhildur, and Hildur Ýr Hilmarsdottir. "Genetic Risk Factors of Depression." In Depression, edited by Sonia Israel, David Benrimoh, Sylvanne Daniels, and Gustavo Turecki, 33–50. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780190929565.003.0003.
Повний текст джерелаAllendorf, Fred W., W. Chris Funk, Sally N. Aitken, Margaret Byrne, and Gordon Luikart. "Quantitative Genetics." In Conservation and the Genomics of Populations, 223–52. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198856566.003.0011.
Повний текст джерелаAbdallah, Sarah B., and Thomas V. Fernandez. "Genetic Susceptibility in Tourette Syndrome." In Tourette Syndrome, edited by Sarah B. Abdallah and Thomas V. Fernandez, 125–36. 2nd ed. Oxford University Press, 2022. http://dx.doi.org/10.1093/med/9780197543214.003.0009.
Повний текст джерелаТези доповідей конференцій з теми "Genome-Wide polygenic score"
Thomas, Minta, Lori C. Sakoda, Jeffrey K. Lee, Mark A. Jenkins, Andrea Burnett-Hartman, Heather Hampel, Elisabeth A. Rosenthal, et al. "Abstract 881: Benchmarking genome-wide polygenic risk score development techniques in colorectal cancer risk prediction." In Proceedings: AACR Annual Meeting 2021; April 10-15, 2021 and May 17-21, 2021; Philadelphia, PA. American Association for Cancer Research, 2021. http://dx.doi.org/10.1158/1538-7445.am2021-881.
Повний текст джерелаDarst, Burcu F., Ravi K. Madduri, Alexis A. Rodriguez, Xin Sheng, Rosalind A. Eeles, Zsofia Kote-Jarai, John M. Gaziano, Amy C. Justice, David V. Conti, and Christopher A. Haiman. "Abstract PO-163: Genome-wide polygenic risk score of prostate cancer in African and European ancestry men." In Abstracts: AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; October 6-8, 2021. American Association for Cancer Research, 2022. http://dx.doi.org/10.1158/1538-7755.disp21-po-163.
Повний текст джерелаЗвіти організацій з теми "Genome-Wide polygenic score"
Zeng, Yi, Huashuai Chen, Xiaomin Liu, Rui Ye, Enjun Xie, Zhihua Chen, Jiehua Lu, et al. Sex differences in genetic associations with longevity in Han Chinese: sex-stratified genome-wide association study and polygenic risk score analysis. Rostock: Max Planck Institute for Demographic Research, February 2017. http://dx.doi.org/10.4054/mpidr-wp-2017-004.
Повний текст джерелаSela, Hanan, Eduard Akhunov, and Brian J. Steffenson. Population genomics, linkage disequilibrium and association mapping of stripe rust resistance genes in wild emmer wheat, Triticum turgidum ssp. dicoccoides. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598170.bard.
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