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  "Title": "Compute and Visualize Bivariate Associations",
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  "Description": "Pearson and Spearman correlation coefficients are commonly\nused to quantify the strength of bivariate associations of\ngenomic variables.  For example, correlations of gene-level DNA\ncopy number and gene expression measurements may be used to\nassess the impact of DNA copy number changes on gene expression\nin tumor tissue.  'MVisAGe' enables users to quickly compute\nand visualize the correlations in order to assess the effect of\nregional genomic events such as changes in DNA copy number or\nDNA methylation level.  Please see Walter V, Du Y, Danilova L,\nHayward MC, Hayes DN, 2018. Cancer Research\n<doi:10.1158/0008-5472.CAN-17-3464>.",
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      "title": "A Function for Creating a List of Pearson Correlation Coefficients",
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      "title": "A Function for Plotting Smoothed Pearson Correlation Coefficients Genomewide",
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      "title": "A Function for Plotting Pearson Correlation Coefficients in a Given Genomic Region",
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      "title": "R packages: Static PDF vignettes",
      "engine": "R.rsp::asis",
      "headings": [],
      "created": "2017-05-28 05:17:37",
      "modified": "2017-05-28 05:17:37",
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