/grafify

Easy grafs, ANOVAs and posthoc comparisons.

Primary LanguageR

Installation

To install this package use the following steps. You’ll need the package remotes installed first, skip to the second step if you already have it.

install.packages("remotes") #install remotes
remotes::install_github("ashenoy-cmbi/grafify@*release", dependencies = T) #install latest release with dependencies

grafify depends on ggplot2, lmerTest, emmeans, car, pbkrtest, tidyr, purrr and Hmisc packages.

Motivation

The main goals of this package, besides making it easier for me to share data and functions for the statistics workshop, are the following:

  1. easily make common types of graphs based on ggplot2 but with fewer lines of code
  2. carry out ANOVA analysis using linear models (lm) and mixed effects (lmer)
  3. perform post-hoc comparisons (through emmeans)
  4. simulate one-way and two-way ANOVA design data for power analysis

If you’re interested in basic theory and code for stats in R, also visit Statistics for Micro/Immuno Biologists.

Latest version: v1.4.1

Features

grafify has four main kinds of functions as follows.

  1. There are 19 plot_ functions of 6 broad types in grafify. The plot_scatter.. versions are preferred when there are many data points, plot_dot.. versions have a “cleaner” layout for smaller datasets.

    1. Two categorical variables: these graphs either use scatter (or also called jitter) or dot plot geometries: plot_scatterbar_sd, plot_scatterbox, plot_scatterviolin and plot_dotbar_sd, plot_dotbox, plot_dotviolin
    2. Three or four categorical variables: plot_3d_scatterbar, plot_3d_scatterbox, plot_4d_scatterbar, plot_4d_scatterbox
    3. Quantitative X-Y & a third variable: plot_xy_NumGroup, plot_xy_CatGroup
    4. Matched before-after graphs: plot_befafter_colours, plot_befafter_shapes
    5. Data distributions: plot_qqline, plot_density plot_histogram
    6. Summary graphs with SD error bars: plot_bar_sd, plot_point_sd

The following qualitative and continuous palettes are implemented in grafify:

(The continuous colour scheme based on Paul Tol’s YlOrBl variant is new in v0.2.0.)

  1. Fitting linear models and linear mixed models and obtaining ANOVA tables

    1. linear models for ordinary ANOVAs: simple_anova, simple_model,
    2. linear mixed effects ANOVAs: mixed_anova, mixed_model

  2. Perform post-hoc comparisons based on fitted models

    1. posthoc_Pariwise
    2. posthoc_Levelwise
    3. posthoc_vsRef

  3. Generating random one-way and two-way data based on mean and SD.

    1. one-way designs: make_1way_data, make_1way_rb_data
    2. two-way designs: make_2way_data, make_2way_rb_data

  4. Colour-blind compatible schemes:

    1. okabe_ito (see Mike Mol’s blog).
    2. bright, pale, muted, dark, light, vibrant, and contrast colours (see Paul Tol’s blog).

Vignettes

Visit the grafify vignettes website for detailed examples of usage.

Release notes

Full reference to all functions available at grafify pages.

New in v1.4.1

This version “breaks” a few arguments from v0.3.1, therefore is v1.4.1. Specifically, opacity for both symbols and bars/boxes/violins can be set using s_alpha and b_alpha or v_alpha, respectively; previously, only bars/boxes/violin opacity could be set with a single alpha parameter. Old code with just alpha will no longer work, sorry! There are also new graph types and arguments for ANOVAs as below.

  1. New graph types

    1. plot_density and plot_histogram for smooth density or histogram plots through geom_density and geom_histogram respectively.
    2. two new plot types plot_scatterbox and plot_scatterviolin that complement the plot_dot... versions and instead use geom_point with position_jitter. These versions are useful when a large number of data points are needed to be plotted.

  2. Updates

    1. simple_anova where the table also has Mean SS.
    2. mixed_anova now has two new arguments, one to change method for Df calculation and second to get type I or III SS (default is type II).
    3. jitter argument added to plot_3d.. and plot_4d.. functions for consistency with other scatter plots.
    4. bwid argument (for adjusting width of bars) added to plot_scatterbar_sd for consistency.

New in v0.3.1

Bug fixes in mixed_model and simple_model which now correctly lists the data used in the call field.

New in v0.3.0

  1. A new plot_4d_scatterbar function which is like plot_4d_scatterbox but plots bar and SD. So there are now two plot_3d_ and plot_4d_ functions.
  2. Text on X-axis on all graphs can be rotated from 0-90 using TextXAngle argument to prevent overlap.
  3. plot_dot_ functions now have dotthick option to set stroke thickness. This is similar to symthick for scatter/jitter plots.
  4. Using facet_wrap or facet_grid will not draw a box around panel text (unlike the default in theme_classic()).
  5. plot_3d_ and plot_4d_ functions draw symbols in black colour.

Fixed in v0.2.1:

  1. Bug fixes in plot_3d_scatterbar and plot_3d_scatterbox, which now correctly use the “shapes” variable to fill colour of bars/boxes and shape of the symbols; symbols are depicted in black.
  2. simple_anova generates type II ANOVA table through car::Anova(), so the car package is now a dependency. v0.1.0 and v0.2.0 generated type I ANOVA table through stats::anova().

New in v0.2.0:

  1. the main difference from v0.1.0 is that all plot_ functions apply the all_grafify colour scheme by default (see plot_ vignettes on how to change colours)
  2. two new types of graphs are possible with two quantitative X-Y plots with a third variable that is either numeric (plot_xy_NumGroup) or categorical (plot_xy_CatGroup).
  3. there are two new continuous colour schemes (scale_fill_grafify_c and scale_colour_grafify_c), based on Paul Tol’s variant of YlOrBl scheme.