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10.1016/j.gpb.2020.06.001 http://scihub22266oqcxt.onion/10.1016/j.gpb.2020.06.001 32663617!7354277!32663617     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Genomics+Proteomics+Bioinformatics 2020 ; 18 (6): 640-647 Nephropedia Template TP {{tp|p=32663617|t=2020. Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling Bias and Infection Clusters |pdf=|usr=}}{{32663617}} gab.com Text Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling Bias and Infection Clusters JO: Genomics Proteomics Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=32663617 #FOAvip A novel RNA virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the ongoing outbreak of coronavirus disease 2019 (COVID-19). Population genetic analysis could be useful for investigating the origin and evolutionary dynamics of COVID-19. However, due to extensive sampling bias and existence of infection clusters during the epidemic spread, direct applications of existing approaches can lead to biased parameter estimations and data misinterpretation. In this study, we first present robust estimator for the time to the most recent common ancestor (TMRCA) and the mutation rate, and then apply the approach to analyze 12,909 genomic sequences of SARS-CoV-2. The mutation rate is inferred to be 8.69 x 10(-4) per site per year with a 95% confidence interval (CI) of [8.61 x 10(-4), 8.77 x 10(-4)], and the TMRCA of the samples inferred to be Nov 28, 2019 with a 95% CI of [Oct 20, 2019, Dec 9, 2019]. The results indicate that COVID-19 might originate earlier than and outside of Wuhan Seafood Market. We further demonstrate that genetic polymorphism patterns, including the enrichment of specific haplotypes and the temporal allele frequency trajectories generated from infection clusters, are similar to those caused by evolutionary forces such as natural selection. Our results show that population genetic methods need to be developed to efficiently detangle the effects of sampling bias and infection clusters to gain insights into the evolutionary mechanism of SARS-CoV-2. Software for implementing VirusMuT can be downloaded at https://bigd.big.ac.cn/biocode/tools/BT007081. Twit Text FOAVip Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling Bias and Infection Clusters ????Genomics Proteomics Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=32663617 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32663617 #FOAvip English Wikipedia <ref>{{Cite pmid|32663617}}</ref> Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling Bias and Infection Clusters #MMPMID32663617 Liu Q; Zhao S; Shi CM; Song S; Zhu S; Su Y; Zhao W; Li M; Bao Y; Xue Y; Chen H Genomics Proteomics Bioinformatics 2020[Dec]; 18 (6): 640-647 PMID32663617show ga A novel RNA virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the ongoing outbreak of coronavirus disease 2019 (COVID-19). Population genetic analysis could be useful for investigating the origin and evolutionary dynamics of COVID-19. However, due to extensive sampling bias and existence of infection clusters during the epidemic spread, direct applications of existing approaches can lead to biased parameter estimations and data misinterpretation. In this study, we first present robust estimator for the time to the most recent common ancestor (TMRCA) and the mutation rate, and then apply the approach to analyze 12,909 genomic sequences of SARS-CoV-2. The mutation rate is inferred to be 8.69 x 10(-4) per site per year with a 95% confidence interval (CI) of [8.61 x 10(-4), 8.77 x 10(-4)], and the TMRCA of the samples inferred to be Nov 28, 2019 with a 95% CI of [Oct 20, 2019, Dec 9, 2019]. The results indicate that COVID-19 might originate earlier than and outside of Wuhan Seafood Market. We further demonstrate that genetic polymorphism patterns, including the enrichment of specific haplotypes and the temporal allele frequency trajectories generated from infection clusters, are similar to those caused by evolutionary forces such as natural selection. Our results show that population genetic methods need to be developed to efficiently detangle the effects of sampling bias and infection clusters to gain insights into the evolutionary mechanism of SARS-CoV-2. Software for implementing VirusMuT can be downloaded at https://bigd.big.ac.cn/biocode/tools/BT007081. |*COVID-19[MESH] |*SARS-CoV-2[MESH] |Genetics, Population[MESH] |Haplotypes[MESH] |Humans[MESH]Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling B(epmc).pdf DeepDyve Pubget Overpricing