Adk evolvability data and analysis scripts

Overview A collection of scripts for quantifying doubling time and population diversity via Nanopore sequencing. All scripts were run in Spyder using conda 24.11.3. Code Usage Turbidostat analysis python analyze_turbidostat.py Running this script will output a csv file with doubling times calculated from growth of OD-regulated cultures in a Chi.Bio turbidostat. Nanopore sequencing data analysis Raw fastq reads obtained from Plasmidsaurus were analyzed via the longread_umi pipeline: https://github.com/SorenKarst/longread_umi Output consensus file is used as the input for analyze_vars.py. Running this script requires biopython ≤ 1.84 for use of the MafftCommandLine wrapper. It will output intermediate fasta and csv files for each replicate in the dataset: output_condensed.csv is the output of condensing all amplicons from longread_umi output into a dataframe of unique sequences, with a column that counts how many times each sequence is found. MAFFT.fasta is the output of MafftCommandLine wrapper, which aligns each sequence in output_condensed.csv to a reference regions.csv is the output of splitting each amplicon into regions (e.g., promoter, RBS, CDS, etc.). cleaned.csv is the output after removing contaminating sequences from the dataset, that may be introduced during any of the sample preparation steps. mut_name.csv is the output that names each sequence with respect to the reference (e.g., V4M for a valine to methionine substitution at position 4 of the Adk gene). Note that in regions with repeated nucleotides, if gaps or insertions occur the assignent of the position of the gap/deletion is arbitrary. For example, a deletion of a cytosine in the sequence ACCCA could be defined as C2del, C3del, or C4 del. vars_avg.csv is the final output. Frequencies of all replicates are averaged together in a single csv that is easy to plot.