# Kamil Slowikowski

#### 6 packages on CRAN

#### 1 packages on Bioconductor

Provides text and label geoms for 'ggplot2' that help to avoid overlapping text labels. Labels repel away from each other and away from the data points.

Generate area-proportional Euler diagrams using numerical optimization. An Euler diagram is a generalization of a Venn diagram, relaxing the criterion that all interactions need to be represented. Diagrams may be fit with ellipses and circles via a wide range of inputs and can be visualized in numerous ways.

Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Specialization of method ggplot(): accept and convert on the fly time series data. Geom: "table", "plot" and "grob" add insets to plots using native data coordinates, while "table_npc", "plot_npc" and "grob_npc" do the same using "npc" coordinates through new aesthetics "npcx" and "npcy". Statistics: locate and tag peaks and valleys; count observations in different quadrants of a plot; select observations based on 2D density; label with the equation of a polynomial fitted with lm() or other types of models; labels with P-value, R^2 or adjusted R^2 or information criteria for fitted models; label with ANOVA table for fitted models; label with summary for fitted models. Model fit classes for which suitable methods are provided by package 'broom' are supported. Scales and stats to build volcano and quadrant plots based on outcomes, fold changes, p-values and false discovery rates.

Provides a word cloud text geom for 'ggplot2'. Texts are placed so that they do not overlap as in 'ggrepel'. The algorithm used is a variation around the one of 'wordcloud2.js'.

A wrapper for the 'Highcharts' library including shortcut functions to plot R objects. 'Highcharts' <http://www.highcharts.com/> is a charting library offering numerous chart types with a simple configuration syntax.

Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.

This package implements the remove unwanted variation (RUV) methods of Risso et al. (2014) for the normalization of RNA-Seq read counts between samples.