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This site contains the raw data, analyzed data sets, and computer code used to generate figures in the main text and all supplementary figures and tables when applicable. All files necessary to regenerate these figures and tables all available on this OSF page, and we explicitly state their file name below. Please note that all raw sequencing files in FASTQ format are available on the SRA Archive: [**BioProject PRJNA451489**][2]. Figures ======= Figure 1. Fluorescent protein signal is proportional to gene copy number. ------------------------------------------------------------------------ To generate Figure1A Raw data: `Flow_cytometry/Figure_1_data/Raw_data` Script used to generate figure: `Flow_cytometry/Figure_1_data/Figure_1_pub` Figure 2. Dynamics of GAP1 CNVs in evolving populations. -------------------------------------------------------------- Data files: `Flow_cytometry/Figure_2_data` Script used to generate figure: `Flow_cytometry/Figure_2_data/Figure_2_pub` Figure 3. Diversity and fitness effects of GAP1 CNVs. ----------------------------------------------------------- **3B and 3C were generated using data from `S4 Table`** Other data files: `Sequencing_data/Figure_3_data/sample_76_RD.txt` Script used to generate figure: `Sequencing_data/Figure_3_data/Figure_3_pub` Figure 4. Interrupted inverted repeats mediate CNV formation. ------------------------------------------------------------------- Data files: `Sequencing_data/Breakpoint_detection/Breakpoint_inverted_repeat_features.txt` Figure 5. Lineage tracking reveals extensive clonal interference among CNV-containing lineages. ------------------------------------------------------------------------ Raw data: Barcode sequencing files on SRA Data files: `Flow_cytometry/SLGating03202018_GADATA.csv` `Sequencing_data/Barcode_seq_and_scripts` Script used to generate figure B: `Sequencing_data/Barcode_seq_and_scripts/Barcode_sequencing.Rmd` Supplementary Text ================== S1 Text. Calculation of CNV dynamics parameters. ------------------------------------------------ Data files: `Flow_cytometry/Figure_2_data/FlowAnalysisSumm_FINAL.csv` Script: `Flow_cytometry/Generate S1 Text.Rmd` S2 Text. Analysis of GAP1 and DUR3 CNVs. ---------------------------------------- Script: `Sequencing_data/Read_depth_plots/Generate S2 Text.Rmd` S3 Text. Existing CNV detection algorithm performance. ------------------------------------------------------ See `Sequencing_data/Algorithm_performance` for zipped files and metadata Supplementary Figures ===================== UNLESS OTHERWISE SPECIFIED, ALL SUPPLEMENTARY FIGURES WERE GENERATED USING THE CODE IN THE SCRIPT: `GenerateSFigs.R`. S1 Fig. Assessment of CNV reporter fitness effects. --------------------------------------------------- Data files: `Fitness_assays/Fitness_Final.csv` S2 Fig. The GAP1 CNV reporter indicates the emergence of GAP1 CNVs in all glutamine-limited populations. ------------------------------------------------------------------------ Data files: `Flow_cytometry/Figure_2_data/SingleCellDistributions.txt` S3 Fig. Normalization by forward scatter mitigates effects of cell physiology and morphology variation on CNV reporter signal. ------------------------------------------------------------------------ Data files: `Flow_cytometry/Figure_2_data/FlowAnalysisSumm_FINAL.csv` S4 Fig. Gating flow cytometry data enables estimation of CNV alleles that contain more than two copies. ------------------------------------------------------------------------ Data files: `Flow_cytometry/Figure_2_data/FlowAnalysisSumm_FINAL.csv` S5 Fig. Pulsed-field gel electrophoresis for molecular characterization of GAP1 CNVs. ------------------------------------------------------------------------ N/A S6 Fig. GAP1 CNV-containing lineages have a higher relative fitness than the ancestral strain. ------------------------------------------------------------------------ Data files: `Fitness_assays/Fitness_Final.csv` S7 Fig. Identification of CNV alleles at the DUR3 locus. -------------------------------------------------------- Data files: `S4 Table` S8 Fig. Benchmarking existing CNV detection algorithms with simulated clonal samples. ------------------------------------------------------------------------ Data files: `Sequencing_data/Algorithm_performance/Algorithm_Scores.xlsx` Script: `Sequencing_data/Algorithm_performance/Generate_plots.R` S9 Fig. Benchmarking existing CNV detection algorithms with simulated heterogeneous populations samples. ------------------------------------------------------------------------ Data files: `Sequencing_data/Algorithm_performance/Algorithm_Scores.xlsx` Script: `Sequencing_data/Algorithm_performance/Generate_plots.R` S10 Fig. Population estimates of GAP1 copy number by CNV reporter and quantitative sequencing are linearly correlated and increase with time of adaptive evolution. ------------------------------------------------------------------------ Data: `S2 Table` S11 Fig. Population prehistory of independent evolution experiments. ------------------------------------------------------------------------ N/A S12 Fig. Distribution of barcode counts in ancestral populations. ----------------------------------------------------------------- Data files: `Sequencing_data/Barcode_seq_and_scripts` Script used to generate figure: `Sequencing_data/Barcode_seq_and_scripts/Barcode_sequencing.Rmd` S13 Fig. Identification of barcoded GAP1 CNV-lineages in evolving populations. ------------------------------------------------------------------------ Data files: 1. `Sequencing_data/Barcode_seq_and_scripts` 2. `Flow_cytometry/SLGating03202018_GADATA.csv` Script used to generate figure: `Sequencing_data/Barcode_seq_and_scripts/Barcode_sequencing.Rmd` S14 Fig. FACS reports for isolation of CNV subpopulation. --------------------------------------------------------- N/A [2]:
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