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Most genes encode for proteins that ultimately control cellular function. Understanding the interrelation between genes without the application of statistical methods can be a daunting task. Correlation analysis is a powerful approach to determine the strength of association between two variables (e.g., gene-wise expression). Moreover, it becomes essential to visualize this data to establish patterns and derive insight. The most common method for gene expression visualization is to use correlation heatmaps in which the colors of the plot represent strength of co-expression. In order to address this requirement, we developed a visualization tool called BioCPR: Biological Correlation Plots in R. This tool performs both correlation analysis and subsequent visualization in the form of an interactive heatmap, improving both usability and interpretation of the data. 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The Molecular Taxonomy of Primary Prostate Cancer. Cell, 163, 1011\u20131125."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1158\/2159-8290.CD-12-0095","article-title":"The CBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data","volume":"2","author":"Ethan","year":"2012","journal-title":"Cancer Discov."},{"key":"ref_4","unstructured":"Winston, C., Cheng, J., Allaire, J.J., Sievert, C., Schloerke, B., Xie, Y., Allen, J., McPherson, J., Dipert, A., and Borges, B. (2021). Shiny: Web Application Framework for R. CRAN, Available online: https:\/\/cran.r-project.org\/package=shiny."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"593","DOI":"10.4103\/0019-5154.193662","article-title":"Biostatistics Series Module 6: Correlation and Linear Regression","volume":"61","author":"Avijit","year":"2016","journal-title":"Indian J. Dermatol."},{"key":"ref_6","unstructured":"Alboukadel, K. (2019). Ggcorrplot: Visualization of a Correlation Matrix Using \u2018Ggplot2\u2019. CRAN, Available online: https:\/\/cran.r-project.org\/package=ggcorrplot."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1093\/biomet\/30.1-2.81","article-title":"A New Measure of Rank Correlation","volume":"30","author":"George","year":"1938","journal-title":"Biometrika"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2316","DOI":"10.1093\/bib\/bby076","article-title":"Impact of Similarity Metrics on Single-Cell RNA-Seq Data Clustering","volume":"20","author":"Taiyun","year":"2019","journal-title":"Brief. Bioinform."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ming, L.H., Yang, D., Liu, Z.F., Hu, S.Z., Yan, S.H., and He, X.W. (2019). Density Distribution of Gene Expression Profiles and Evaluation of Using Maximal Information Coefficient to Identify Differentially Expressed Genes. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0219551"},{"key":"ref_10","unstructured":"Jeremy, M., and Banyard, P. (2007). Understanding and Using Statistics in Psychology: A Practical Introduction, SAGE Publications Ltd.. Available online: https:\/\/sk.sagepub.com\/books\/understanding-and-using-statistics-in-psychology."},{"key":"ref_11","first-page":"69","article-title":"Statistics Corner: A Guide to Appropriate Use of Correlation Coefficient in Medical Research","volume":"24","author":"Mavuto","year":"2012","journal-title":"Malawi Med. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1126\/science.30.757.23","article-title":"Determination of the Coefficient of Correlation","volume":"30","author":"Karl","year":"1909","journal-title":"Science"},{"key":"ref_13","unstructured":"R Core Team (2020). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: https:\/\/www.r-project.org\/."},{"key":"ref_14","unstructured":"Barret, S., Crowley, J., Cook, D., Wickham, H., Briatte, F., Marbach, M., Thoen, E., Elberg, A., and Larmarange, J. (2021). GGally: Extension to \u2018Ggplot2\u2019. CRAN, Available online: https:\/\/cran.r-project.org\/package=GGally."},{"key":"ref_15","first-page":"101","article-title":"The Proof and Measurement of Association between Two Things","volume":"15","author":"Charles","year":"1904","journal-title":"Am. J. Psychol."},{"key":"ref_16","unstructured":"Statistics Solutions (2021, August 15). Correlation (Pearson, Kendall, Spearman). Statisticssolutions.Com. Available online: https:\/\/www.statisticssolutions.com\/free-resources\/directory-of-statistical-analyses\/correlation-pearson-kendall-spearman\/."},{"key":"ref_17","unstructured":"Taiyun, W., and Simko, V. (2021). R Package \u2018Corrplot\u2019: Visualization of a Correlation Matrix. CRAN, Available online: https:\/\/github.com\/taiyun\/corrplot."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1126\/science.22.558.309","article-title":"The Spearman Correlation Formula","volume":"22","author":"Clark","year":"1905","journal-title":"Science"}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/9\/97\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:58:54Z","timestamp":1760165934000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/9\/97"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,8]]},"references-count":18,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["data6090097"],"URL":"https:\/\/doi.org\/10.3390\/data6090097","relation":{},"ISSN":["2306-5729"],"issn-type":[{"type":"electronic","value":"2306-5729"}],"subject":[],"published":{"date-parts":[[2021,9,8]]}}}