Chunk #39 — Methods — Performance evaluation measurements

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Statistical modeling for sensitive detection of low-frequency single nucleotide variants.

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Precision, recall and F1 score are defined below.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ precision=\frac{number\ of\ recovered\ benchmark\ SNVs}{number\ of\ predicted\ SNVs} $$\end{document}precision=numberofrecoveredbenchmarkSNVsnumberofpredictedSNVs\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ recall=\frac{number\ of\ recovered\ benchmark\ SNVs}{expected\ number\ of\ benchmark\ SNVs} $$\end{document}recall=numberofrecoveredbenchmarkSNVsexpectednumberofbenchmarkSNVs\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ F1=2*\frac{precision* recall}{precision+ recall} $$\end{document}F1=2*precision*recallprecision+recall