Files and scripts used to analyze data and generate figures. Master dataframe and phylogenetic tree filesnameSpecies. csvnameSpecies. xlsxtaxonTimeTree. nwktaxonTimeTreeₐddBranches. nwk Scripts to analyze and plot data for single species or synteny-anchored comparisons between two or three speciesaddBranches. py # add owl and bee branches to treemakeGCtrack. py # for making local GC content tracks used in later analysismakeCpGtrackᵥ2. py # for making CpG density tracks used in later analysismakeRepeatDensityTrackᵥ2. py # for making repeat density tracks used in later analysis (based on default RepeatMasker and Dfam libraries) makeRepeatDensityTrackᵥRepeatModelerSingleChrom. py # for making # for making repeat density tracks used in later analysis (based on de novo libraries) gffCDStoTSV. py # make a CDS density track used in later analysisfindBestCorrelationPC1ᵥ6. py # for determining the Pearson correlation between the Hi-C PC1 and various genomic features (data used primarily in Fig. 2; this also generates data for use in determining length scales) compartmentLengthScaleᵥ5. py # for determining the autocorrelation and characteristic length scales of Hi-C PC1, CDS, and GC content (data used primarily in Fig. 3) compareRepeatModelDensityCompartmentsᵥ1. py # for comparing the repeat modeler librariesodpAnalysis. py # analyze output from ODP pipeline and also compare with LASTZ synteny pipeline, generate summary files with all syntenic CDSfindBiggestColinearityᵥ4. py # analyze syntenic CDS and identify syntenic blocks between 2 speciesfindBiggestColinearityₘultipleᵥ0. py # analyze syntenic blocks between 2 species and identify blocks shared between multiple speciescorrelationHiCdistantᵥ10. py # compare Hi-C PC1 and genomic features on the syntenic blocks shared between two species (used in Fig. 4) correlationHiCdistantquery2ᵥ0. py # compare Hi-C PC1 and genomic features on the syntenic blocks shared between three species (used in Fig. 5) compartmentsExperimentalHiCᵥ3. py # plot Hi-C contact maps and PC1 tracks for each chromosome (used in Fig. 1) plotCompartmentsFeaturesHiCforFig2ᵥ0. py # plot Hi-C contact maps, PC1 tracks, and several genomic features for largest chromosomes (used in Fig. 2, Fig. 3, Ext. Data Fig. 2) Scripts that combine results, analyze, and plotgetFeatureCompareᵥ5. py # for Fig. 2 and Ext. Data Figs. 1, 3, 4, 5, 6 (this also generates the analyzed data used for making the trees in ancPhyToolsfeaturesᵥ2. R) ancPhyToolsfeaturesᵥ2. R # for making the trees with ape and phytools (Figs. 1, 2, 4, 5 and Ext. Data Figs. 3, 5analyzeCompartmentLengthScalesᵥ3. py # for Fig. 3 and Ext. Data Figs. 1, 3, 7correlationHiCₛtatisticsAllᵥ4. py # for Fig. 5plotRepeatMaskerComparisonᵥ1. py # for Ext. Data Fig. 10 (repeat library comparison)
Cerbus et al. (Wed,) studied this question.