Scripts for "Universal link between coding sequence clustering and conserved chromatin compartments"
Files and scripts used to analyze data and generate figures. Master dataframe and phylogenetic tree filesnameSpecies.csvnameSpecies.xlsxtaxonTimeTree.nwktaxonTimeTree_addBranches.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 analysismakeCpGtrack_v2.py # for making CpG density tracks used in later analysismakeRepeatDensityTrack_v2.py # for making repeat density tracks used in later analysis (based on default RepeatMasker and Dfam libraries)makeRepeatDensityTrack_vRepeatModelerSingleChrom.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 analysisfindBestCorrelationPC1_v6.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)compartmentLengthScale_v5.py # for determining the autocorrelation and characteristic length scales of Hi-C PC1, CDS, and GC content (data used primarily in Fig. 3)compareRepeatModelDensityCompartments_v1.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 CDSfindBiggestColinearity_v4.py # analyze syntenic CDS and identify syntenic blocks between 2 speciesfindBiggestColinearity_multiple_v0.py # analyze syntenic blocks between 2 species and identify blocks shared between multiple speciescorrelationHiC_distant_v10.py # compare Hi-C PC1 and genomic features on the syntenic blocks shared between two species (used in Fig. 4)correlationHiC_distant_query2_v0.py # compare Hi-C PC1 and genomic features on the syntenic blocks shared between three species (used in Fig. 5)compartmentsExperimentalHiC_v3.py # plot Hi-C contact maps and PC1 tracks for each chromosome (used in Fig. 1)plotCompartmentsFeaturesHiC_forFig2_v0.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 plotgetFeatureCompare_v5.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 ancPhyTools_features_v2.R)ancPhyTools_features_v2.R # for making the trees with ape and phytools (Figs. 1,2,4,5 and Ext. Data Figs. 3,5analyzeCompartmentLengthScales_v3.py # for Fig. 3 and Ext. Data Figs. 1,3,7correlationHiC_statisticsAll_v4.py # for Fig. 5plotRepeatMaskerComparison_v1.py # for Ext. Data Fig. 10 (repeat library comparison)
Authors
- Kyogo Kawaguchi (ORCID: https://orcid.org/0000-0001-9395-9875)
- Ichiro Hiratani
- Rory Thomas Cerbus
Institutions
- RIKEN (JP)
- RIKEN Center for Biosystems Dynamics Research (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-03-04
- DOI
- https://doi.org/10.5281/zenodo.18332940
- Primary Topic
- Genomics and Chromatin Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00