Publications by Easy Guides
Practical Guide to Cluster Analysis in R – Book
Introduction Large amounts of data are collected every day from satellite images, bio-medical, security, marketing, web search, geo-spatial or other automatic equipment. Mining knowledge from these big data far exceeds human’s abilities. Clustering is one of the important data mining methods for discovering knowledge in multidimensional data. T...
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Text mining and word cloud fundamentals in R : 5 simple steps you should know
Text mining methods allow us to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud, which is a visual representation of text data. The procedure of creating word clouds is very simple in R if you know the different steps to execute. The text mining package (tm...
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Factoextra R Package: Easy Multivariate Data Analyses and Elegant Visualization
factoextra is an R package making easy to extract and visualize the output of exploratory multivariate data analyses, including: Principal Component Analysis (PCA), which is used to summarize the information contained in a continuous (i.e, quantitative) multivariate data by reducing the dimensionality of the data without loosing important inform...
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survminer 0.3.0
I’m very pleased to announce that survminer 0.3.0 is now available on CRAN. survminer makes it easy to create elegant and informative survival curves. It includes also functions for summarizing and inspecting graphically the Cox proportional hazards model assumptions. This is a big release and a special thanks goes to Marcin Kosiński and Przem...
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Survminer Cheatsheet to Create Easily Survival Plots
We recently released the survminer verion 0.3, which includes many new features to help in visualizing and sumarizing survival analysis results. In this article, we present a cheatsheet for survminer, created by Przemysław Biecek, and provide an overview of main functions. survminer cheatsheet The cheatsheet can be downloaded from STHDA and fro...
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fastqcr: An R Package Facilitating Quality Controls of Sequencing Data for Large Numbers of Samples
Introduction High throughput sequencing data can contain hundreds of millions of sequences (also known as reads). The raw sequencing reads may contain PCR primers, adaptors, low quality bases, duplicates and other contaminants coming from the experimental protocols. As these may affect the results of downstream analysis, it’s essential to perfo...
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Add P-values and Significance Levels to ggplots
In this article, we’ll describe how to easily i) compare means of two or multiple groups; ii) and to automatically add p-values and significance levels to a ggplot (such as box plots, dot plots, bar plots and line plots …). Contents: Prerequisites Methods for comparing means R functions to add p-values Compare two independent groups Compare ...
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Facilitating Exploratory Data Visualization: Application to TCGA Genomic Data
In genomic fields, it’s very common to explore the gene expression profile of one or a list of genes involved in a pathway of interest. Here, we present some helper functions in the ggpubr R package to facilitate exploratory data analysis (EDA) for life scientists. Exploratory Data visualization: Gene Expression Data Standard graphical techni...
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Bar Plots and Modern Alternatives
This article describes how to create easily basic and ordered bar plots using ggplot2 based helper functions available in the ggpubr R package. We’ll also present some modern alternatives to bar plots, including lollipop charts and cleveland’s dot plots. Note that, the approach to build a bar plot, using ggplot2 standard verbs, has been desc...
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ggplot2 – Easy way to mix multiple graphs on the same page
To arrange multiple ggplot2 graphs on the same page, the standard R functions – par() and layout() – cannot be used. The basic solution is to use the gridExtra R package, which comes with the following functions: grid.arrange() and arrangeGrob() to arrange multiple ggplots on one page marrangeGrob() for arranging multiple ggplots over multip...
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