The functional insight into the genetics of cardiovascular disease: results from the post-GWAS study by L. O. Bryzgalov, E. E. Korbolina, I. S. Damarov, T. I. Merkulova

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Human Genetics of Diabetic Retinopathy: Current Perspectives by Daniel P. K. Ng

“…Harnessing new genetic technologies and resources such as the upcoming 1000 Genomes Project will help advance this field of research, and potentially lead to a rich harvest of insights into the biological mechanisms underlying this debilitating complication.…”
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Analytical validation of the IBD segment-based tool KinSNP® for human identification applications by Bruce Budowle, Jianye Ge, Lee Baker, Kristen Mittelman, David Mittelman

“…Herein, the tool was validated using simulated pedigree data (up to 9th degree relationships) from five diverse populations from the 1000 Genomes Project. Performance was further tested under conditions of simulated genotyping errors and allele or locus dropout. …”
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Faster model-based estimation of ancestry proportions by Santander, Cindy G., Refoyo Martinez, Alba, Meisner, Jonas

“…We further show that fastmixture runs approximately 30$\times$ faster than ADMIXTURE on both simulated and empirical data from the 1000 Genomes Project such that our model-based approach scales to much larger sample sizes than previously possible.…”
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Effects of Single Nucleotide Polymorphism Marker Density on Haplotype Block Partition by Sun Ah Kim, Yun Joo Yoo

Subjects: “…1,000 Genomes Project…”
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Analysis of unmapped regions associated with long deletions in Korean whole genome sequences based on short read data by Yuna Lee, Kiejung Park, Insong Koh

“…Here, we constructed programs to detect so-called unmapped regions (UMRs, where no reads are mapped on the reference genome), scanned 40 Korean genomes to select UMR long deletion candidates, and compared the candidates with the long deletion break points within the genomes available from the 1000 Genomes Project (1KGP). An average of about 36,000 UMRs were found in the 40 Korean genomes tested, 284 UMRs were common across the 40 genomes, and a total of 37,943 UMRs were found. …”
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Trajectory of human migration: insights from autosomal and non-autosomal variant clustering patterns by Samayeta Sarkar Tuli, Joyatry Sarker, Mrinmoy Saha Roddur, Anik Biswas, Reefa Nawar, Tahmina Akter, Md. Wahid Murad, Abu Ashfaqur Sajib

“…Here, we analyzed over 75 million genetic variants (single nucleotide variants (SNVs) and short insertion-deletion (InDels)) within consecutive 2500000 base pair windows in the autosomal as well as non-autosomal chromosomes of 22 populations in four major geographic regions that are cataloged in the 1000 Genomes Project to understand the clustering patterns of the autosomal and non-autosomal variants. …”
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STICI: Split-Transformer with integrated convolutions for genotype imputation by Mohammad Erfan Mowlaei, Chong Li, Oveis Jamialahmadi, Raquel Dias, Junjie Chen, Benyamin Jamialahmadi, Timothy Richard Rebbeck, Vincenzo Carnevale, Sudhir Kumar, Xinghua Shi

“…Our imputation results on the human 1000 Genomes Project and non-human genomes show that STICI can achieve high imputation accuracy comparable to the state-of-the-art genotype imputation methods, with the additional capability to impute multi-allelic variants and various types of genetic variants. …”
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Flanking monomer repeats define lower context complexity of sites containing single nucleotide polymorphisms in the human genome by N. S. Safronova, M. P. Ponomarenko, I. I. Abnizova, G. V. Orlova, I. V. Chadaeva, Y. L. Orlov

“…We have investigated a mutation frequency within the human genome for the set of known single nucleotide polymorphisms (SNPs) from the “1000 genomes” project. We have developed and applied novel statistical computational methods to analyze genetic text based on its complexity. …”
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The Frequency of <i>DPYD</i> c.557A>G in the Dominican Population and Its Association with African Ancestry by Mariela Guevara, Carla González de la Cruz, Fernanda Rodrigues-Soares, Ernesto Rodríguez, Caíque Manóchio, Eva Peñas-Lledó, Pedro Dorado, Adrián LLerena

“…<b>Methods:</b> For this study, 196 healthy volunteers from the Dominican Republic were genotyped for <i>DPYD</i> variants by qPCR, and individual genomic ancestry analysis was performed in 178 individuals using 90 informative ancestry markers. Data from the 1000 Genomes project were also retrieved for comparison and increased statistical power. …”
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Biomedical and candidate SN P markers of chronopathologies can significantly change affinity of ТАТА -binding protein for human gene promoters by D. A. Rasskazov, N. L. Podkolodnyy, O. A. Podkolodnaya, N. N. Podkolodnaya, V. V. Suslov, L. K. Savinkova, P. M. Ponomarenko, M. P. Ponomarenko

“…Computational analysis of millions of unannotated SNPs from the 1000 Genomes Project may speed up the search for biomedical SNP markers. …”
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Search for signals of positive selection of circadian rhythm genes <i>PER1</i>, <i>PER2</i>, <i>PER3</i> in different human populations by A. I. Mishina, S. Y. Bakoev, A. Y. Oorzhak, A. A. Keskinov, Sh. Sh. Kabieva, A. V. Korobeinikova, V. S. Yudin, M. M. Bobrova, D. A. Shestakov, V. V. Makarov, L. V. Getmantseva

“…Data were analyzed using publicly available data from the 1000 Genomes Project for 23 populations. The Extended Haplotype Homozygosity Score statistical method was chosen to search for traces of selection. …”
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Analysis of mutations in CDC27, CTBP2, HYDIN and KMT5A genes in carotid paragangliomas by E. N. Lukyanova, A. V. Snezhkina, D. V. Kalinin, A. V. Pokrovsky, A. L. Golovyuk, O. A. Stepanov, E. A. Pudova, G. S. Razmakhaev, M. V. Orlova, A. P. Polyakov, M. V. Kiseleva, A. D. Kaprin, A. V. Kudryavtseva

“…Paired histologically normal tissues or blood were unavailable, so potentially germline mutations were excluded from the analysis with strong filtering conditions using 1000 Genomes Project and ExAC databases. In this work, ten genes (ZNF717, CDC27, FRG2C, FAM104B, CTBP2, HLA-DRB1, HYDIN, KMT5A, MUC3A, and PRSS3) characterized by the highest level of mutational load were analyzed. …”
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Candidate SNP markers of changes in the expression levels of the human <i>SCN9A</i> gene as a hub gene for pain generation, perception, response and anesthesia by P. A. Dotsenko, K. A. Zolotareva, R. A. Ivanov, I. V. Chadaeva, N. L. Podkolodnyy, V. A. Ivanisenko, P. S. Demenkov, S. A. Lashin, M. P. Ponomarenko

“…Finally, the ratio of SCN9A upregulating to downregulating SNPs was compared to that for all known human genes estimated by the 1000 Genomes Project Consortium. It was found that SCN9A as a hub gene for pain generation, perception, pain response and anesthesia is acted on by natural selection against its downregulation, to keep the nervous system highly informed on the status of the organism and the environment.…”
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SEAD reference panel with 22,134 haplotypes boosts rare variant imputation and genome-wide association analysis in Asian populations by Meng-Yuan Yang, Jia-Dong Zhong, Xin Li, Geng Tian, Wei-Yang Bai, Yi-Hu Fang, Mo-Chang Qiu, Cheng-Da Yuan, Chun-Fu Yu, Nan Li, Ji-Jian Yang, Yu-Heng Liu, Shi-Hui Yu, Wei-Wei Zhao, Jun-Quan Liu, Yi Sun, Pei-Kuan Cong, Saber Khederzadeh, Pian-Pian Zhao, Yu Qian, Peng-Lin Guan, Jia-Xuan Gu, Si-Rui Gai, Xiang-Jiao Yi, Jian-Guo Tao, Xiang Chen, Mao-Mao Miao, Lan-Xin Lei, Lin Xu, Shu-Yang Xie, Jin-Chen Li, Ji-Feng Guo, David Karasik, Liu Yang, Bei-Sha Tang, Fei Huang, Hou-Feng Zheng

“…The SEAD panel, comprising 22,134 haplotypes and 88,294,957 variants, demonstrates improved imputation accuracy for South Asian populations compared to 1000 Genomes Project, TOPMed, and ChinaMAP panels, with a higher proportion of well-imputed rare variants. …”
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