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travis-ci
<a href="https://github.com/hammerlab/vaxrank/commit/<a class=hub.com/hammerlab/vaxrank/commit/2871bef6962008d4738cacdeab70895db67896e1">2871bef69<a href="https://github.com/hammerlab/vaxrank/commit/2871bef6962008d4738cacdeab70895db67896e1">">Some changes in preparation for computing a minimal epitope report: - making EpitopePrediction a class, moving logistic_epitope_score into its methods, adding a wildtype peptide to its members (reference epitope computation logic borrowed from TESLA code, see https://github.com/hammerlab/tesla/blob/</a><a class="double-link" href="https://github.com/hammerlab/vaxrank/commit/<a class="double-link" href="https://github.com/hammerlab/vaxrank/commit/df7bfdb6241899d9b4fa2bb1dc359c2ad4935979">df7bfdb62</a>">df7bfdb62</a><a href="https://github.com/hammerlab/vaxrank/commit/2871bef6962008d4738cacdeab70895db67896e1">/tesla/cli.py#L81) - adding a predicted_effect() method to MutantProteinFragment, changing a couple places in the code to use that for computing the top priority effect of a variant given a mutant protein fragment; also adding a global_start_pos() method (see same TESLA code for reference) - adding a hook into the CLI to make a min epitope report, not implemented yet - setting --min-epitope-score to 0.0 in the test script so I can see multiple variants
532 of 584 relevant lines covered (91.1%)
0.91 hits per line
Coverage | ∆ | File | Lines | Relevant | Covered | Missed | Hits/Line |
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