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ClockstaRX: Testing Molecular Clock Hypotheses With Genomic Data.

David A DuchêneSebastián DuchêneJosefin StillerRasmus HellerSimon Y W Ho
Published in: Genome biology and evolution (2024)
Phylogenomic data provide valuable opportunities for studying evolutionary rates and timescales. These analyses require theoretical and statistical tools based on molecular clocks. We present ClockstaRX, a flexible platform for exploring and testing evolutionary rate signals in phylogenomic data. Here, information about evolutionary rates in branches across gene trees is placed in Euclidean space, allowing data transformation, visualization, and hypothesis testing. ClockstaRX implements formal tests for identifying groups of loci and branches that make a large contribution to patterns of rate variation. This information can then be used to test for drivers of genomic evolutionary rates or to inform models for molecular dating. Drawing on the results of a simulation study, we recommend forms of data exploration and filtering that might be useful prior to molecular-clock analyses.
Keyphrases
  • genome wide
  • electronic health record
  • big data
  • copy number
  • single molecule
  • dna methylation
  • healthcare
  • gene expression
  • artificial intelligence
  • data analysis
  • health information
  • genome wide association