Selected article for: "comparative analysis and data set"

Author: Foley, Nicole M.; Thong, Vu Dinh; Soisook, Pipat; Goodman, Steven M.; Armstrong, Kyle N.; Jacobs, David S.; Puechmaille, Sébastien J.; Teeling, Emma C.
Title: How and Why Overcome the Impediments to Resolution: Lessons from rhinolophid and hipposiderid Bats
  • Document date: 2014_11_29
  • ID: v8xmnfko_89
    Snippet: To facilitate our comparative analysis of diversification rate in the speciose genera Rhinolophus and Hipposideros, faster evolving mitochondrial markers Cyt b and Cox1 were used to enable species level differentiation. To explore if the rate of diversification was marker specific, all available Cyt b and Cox1 sequences for Rhinolophus and Hipposideros species were downloaded from GenBank (April 30, 2013). Four data sets were prepared for the div.....
    Document: To facilitate our comparative analysis of diversification rate in the speciose genera Rhinolophus and Hipposideros, faster evolving mitochondrial markers Cyt b and Cox1 were used to enable species level differentiation. To explore if the rate of diversification was marker specific, all available Cyt b and Cox1 sequences for Rhinolophus and Hipposideros species were downloaded from GenBank (April 30, 2013). Four data sets were prepared for the diversification analysis: 1) Rhinolophus-Cyt b; 2) Rhinolophus-Cox1; 3) Hipposideros-Cyt b, and 4) Hipposideros-Cox1. The four data sets were subsequently aligned using MAFFT v.7 alignment server (Katoh and Standley 2013) . Sequences with 100% identity were identified and removed using CD-HIT server (Huang et al. 2010) . Because of the high number of sequences of conspecifics, sequences with 97.5% sequence identity or above were removed from the data set in an attempt to keep only one sequence per species; 97.5% was used as the cutoff as low intraspecific mtDNA sequence divergence between 1% and 2.5% have been generally reported for bats (Ditchfield 2000) . Data sets were then visually inspected to remove misidentified sequences and trimmed leaving one outgroup species. jModeltest was used to identify the most appropriate model of sequence evolution for each data set using the AIC, which resulted in the selection of GTR+I+G variants for all data sets. Gene trees for each gene fragment were generated in BEAST using the same parameters as previously described. LTT plots were constructed for each data set and compared in R 2.5.2 (R Development Core Team 2012) using the APE package (Paradis et al. 2004) . A nonparametric K-S statistical test was implemented in R 2.5.2 to detect significant difference between the rates of diversification inferred from the LTT plots of the Rhinolophus and Hipposideros genera.

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