Isoswitching drives the aging process in human brains - Data and models

Contents input_filesContains all transcript quantification results and associated sample metadata for the datasets analyzed in this study. Also includes the list of the top 1,000 most predictive genes identified by the model in the file _imp_genes.txt. SPIT_analysisResults from DTU analysis comparing prenatal and postnatal LIBD brain samples. model_source.ipynbMain analysis notebook for isoform trajectories and brain age prediction models using LIBD data. Also includes validation on the Cardoso-Moreira brain dataset and GTEx heart samples. Software requirements: numpy>=1.21.0pandas>=1.3.0scipy>=1.7.0matplotlib>=3.4.0seaborn>=0.11.0scikit-learn>=0.24.0 Run time: ~ 1 hr coverage.bigwig files showing stage-specific read coverage. These can be visualized in IGV. func_analysisProtein-level comparison of isoform pairs from 1,000 predictive genes. Contains:Pairwise alignmentsIsoform-specific coordinatesStructural domain annotations via Foldseek (CATH50)func_analysis_table.tsv with top domain hits for 134 isoform-specific sequences