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Prediction of optimal sequence similarity cut-offs for classification and clustering of metabarcoding data using vsearch global alignment and F-measure optimisation as a confidence measure
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38
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fix(dereplicate_lca): replace NA/empty taxonomy ranks with unclassified
e3b316fView on GitHubfix(compute_sim) Changed incorrect args minsim -> min_sim & ncpu -> n_cpu
e19d0e6View on GitHubfix(reformat): strip parentheses from fully-wrapped genus names
2f31936View on GitHubfix(compute_sim): replace base R I/O with data.table to fix OOM
4c80afeView on GitHubfix(04_prepare_subsets): remove stale fasta_in arg and uncomment ITS1/ITS2 runs
c238c49View on GitHubrefactor(predict): update max_proportion default (0.5→1) and max_seq_no default (25000→20000) to match dnabarcoder defaults
b6ac7b2View on GitHubrefactor(predict): update max_proportion default (0.5→1) and max_seq_no default (25000→20000) to match dnabarcoder defaults
95c2b4bView on GitHubrefactor(subset): remove unique-sequence step and switch to pure random sampling
7b1f4a5View on GitHubfeat: add length_filter and dereplicate_lca to pipeline
1ace343View on GitHubfeat: add length_filter and dereplicate_lca to pipeline
c55b557View on GitHubfeat: add length_filter and dereplicate_lca to pipeline
f45eb96View on GitHubrefactor(subset): species-weighted sampling and species-identified pre-filter
209d71aView on GitHubfix: remove parenthesis-to-double-underscore replacement from reformat.R
4696fe8View on GitHubfeat: extend is_identified() to exclude spikes, prokaryotes, and organelles from prediction
04703ddView on GitHub