ClockstaRX: Testing Molecular Clock Hypotheses With Genomic Data
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ClockstaRX : Testing Molecular Clock Hypotheses With Genomic Data. / Duchêne, David A.; Duchêne, Sebastián; Stiller, Josefin; Heller, Rasmus; Ho, Simon Y. W.
In: Genome Biology and Evolution, Vol. 16, No. 4, evae064, 2024.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - ClockstaRX
T2 - Testing Molecular Clock Hypotheses With Genomic Data
AU - Duchêne, David A.
AU - Duchêne, Sebastián
AU - Stiller, Josefin
AU - Heller, Rasmus
AU - Ho, Simon Y. W.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
U2 - 10.1093/gbe/evae064
DO - 10.1093/gbe/evae064
M3 - Journal article
C2 - 38526019
VL - 16
JO - Genome Biology and Evolution
JF - Genome Biology and Evolution
SN - 1759-6653
IS - 4
M1 - evae064
ER -
ID: 386936692