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Bioinformatics with R Cookbook by Paurush Praveen Sinha

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Visualizing data

Data is more intuitive to comprehend if visualized in a graphical format rather than in the form of a table, matrix, text, or numbers. For example, if we want to visualize how the sepal length in the Iris flower varies with the petal length, we can plot along the x and y axes, respectively, and visualize the trend or even the correlation (scatter plot).In this recipe, we look at some common way of visualizing data in R and plotting functions with R Base graphics functions. We also discuss the basic plotting functions. These plotting functions can be manipulated in many ways, but discussing them is beyond the scope of this book. To get to know more about all the possible arguments, refer to the corresponding help files.

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