Efficient Isolate Selection for Deep Sequencing using Variable-length Markov Chains

VLMC_DiverseIsolateSelection Dataset of simulated sequencing experiments used in the study “Efficient Isolate Selection for Deep Sequencing using Variable-length Markov Chains.” single-end-1-100.zip: 100 shallow, single-end simulation series named single-end-{series} for series 1–100. Represents the multiplexed shallow screening step before VLMC construction and isolate selection. vlmcs.zip: 100 series of learned VLMC bintree models per isolate. vlmc_comparisons.zip: 100 series of pairwise VLMC dissimilarity CSVs and a 167×167 matrix CSV used as input to the selection strategies. selections.zip: 100 series of selection JSONs for all strategies (Random, Greedy MinMax, Greedy MaxDet, Conditional DPP, Hybrid DPP+MCMC). 40-fold-single-end.zip: Simulated single-end deep sequencing reads at 40× coverage, used for evaluation (k-mer richness/entropy on deep reads). 40-fold_kmc_dbs.zip: KMC3 databases produced from the 40× deep reads (one database per isolate), with a TXT version of each database. diversity_evaluations.zip: 100 series of diversity metric outputs (richness/entropy vs cost) derived from selections and deep reads.