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README.md: Should provide example output.
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README.md

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@@ -29,14 +29,41 @@ Pkg.add("RepertoireMetrics")
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```julia
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using RepertoireMetrics
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# Read and analyze a repertoire
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rep = read_repertoire("data.tsv", VJCdr3Definition())
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# Read a repertoire file (supports .tsv and .tsv.gz)
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rep = read_repertoire("sample-001.tsv.gz", VJCdr3Definition();
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length_column=:cdr3)
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```
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# Compute all metrics (default)
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metrics = compute_metrics(rep)
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```
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Repertoire{Int64}:
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Donor: sample-001
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Lineages: 15420
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Total count: 198350
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Top 5 lineages:
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IGHV3-23*01|IGHJ4*02|GCGAGAGATCTTGACTACTGGGGCCAGGGAACC: 856 (0.43%)
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IGHV4-39*01|IGHJ5*02|TGTGCGAGAGTCGATTACTATGATAGTAGTGGT: 724 (0.37%)
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IGHV1-69*01|IGHJ3*02|GCGAGAGATAGTGGCTACGATTTTGACTACTGG: 512 (0.26%)
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IGHV5-51*01|IGHJ4*02|TGTGCGAGACATATTGTGGTGGTAACTGCCCC: 398 (0.2%)
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IGHV3-48*01|IGHJ6*02|GCGAGAGGGGATAGCAGCAGCTGGTACTTTGAC: 287 (0.14%)
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... and 15415 more
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```
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```julia
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# Compute selected metrics using the composable + operator
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metrics = compute_metrics(rep, Depth() + SimpsonDiversity() + Clonality() + GiniCoefficient())
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```
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```
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Metrics (4 computed):
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depth: 198350.0
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simpson_diversity: 0.9997
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clonality: 0.0612
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gini_coefficient: 0.548
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```
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# Or select specific metrics
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metrics = compute_metrics(rep, ShannonEntropy() + Clonality() + D50())
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```julia
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# Or compute all available metrics (default)
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metrics = compute_metrics(rep)
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```
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## Documentation

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