Author: Anthony, Simon J.; Johnson, Christine K.; Greig, Denise J.; Kramer, Sarah; Che, Xiaoyu; Wells, Heather; Hicks, Allison L.; Joly, Damien O.; Wolfe, Nathan D.; Daszak, Peter; Karesh, William; Lipkin, W. I.; Morse, Stephen S.; Mazet, Jonna A. K.; Goldstein, Tracey
Title: Global patterns in coronavirus diversity Document date: 2017_6_12
ID: tboc6zyd_10
Snippet: Coronavirus sequences from the Quan and Watanabe datasets were aligned with reference sequences collected from GenBank using MUSCLE (Edgar 2004) , followed by manual alignment in Se-Al v2.0a11 (http://tree.bio.ed.ac.uk). The best-fitting model of nucleotide substitution for each dataset was selected by Akaike's Information Criterion (AIC) using jModeltest v2.1.5 (Darriba et al. 2012) . For both alignments, the general time reversible model with a.....
Document: Coronavirus sequences from the Quan and Watanabe datasets were aligned with reference sequences collected from GenBank using MUSCLE (Edgar 2004) , followed by manual alignment in Se-Al v2.0a11 (http://tree.bio.ed.ac.uk). The best-fitting model of nucleotide substitution for each dataset was selected by Akaike's Information Criterion (AIC) using jModeltest v2.1.5 (Darriba et al. 2012) . For both alignments, the general time reversible model with a gamma distribution of rate heterogeneity was the best-fitting model. Maximum likelihood trees were constructed from each alignment using MEGA v6.06 (Tamura et al. 2013) . Histograms of all pairwise sequence identities (%) were plotted, as described previously for hantaviruses (Maes et al. 2009) , and used to define cut-offs between viral sequence clusters for analysis (akin to operating taxonomic units).
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