Data Visualisation on 'Lifemap' Tree.

LifemapR

An R package to visualise data on a Lifemap base (https://lifemap.cnrs.fr/)

Installation

To install the development version of LifemapR from GitHub :

remotes::install_github("damiendevienne/LifemapR")

Once installed, load the package with :

require("LifemapR")

Usage

Here is a brief introduction on how to use LifemapR.

1. With the build_Lifemap function transform your already existing data into a format usable by LifemapR functions

data(eukaryotes_1000)

# Construction of a LifemapR usable dataframe
LM_obj <- LifemapR::build_Lifemap(eukaryotes_1000)

After the build_Lifemap function the result is a LifemapR format containing a dataframe :

full_df <- LM_obj$df

2. Then you can display a map with wanted informations by calling one ore more LifemapR functions. Note that with the LifemapR functions, a shiny application will be launched

# Initialise a visualisation for LM_obj
lifemap(LM_obj) +
    # adding a subtree with colored branches
    LifemapR::lm_branches(var_col = "Protein", FUN = mean, col = "PiYG")+
    # adding a set of points
    LifemapR::lm_markers(radius = "GC.", var_fillColor = "Genes", FUN = mean)

Development

To do list :

• [ ] New protocole to fetch data with improved databases (parquet format)

• [ ] Improve create_matrix() to use less CPU (merge before joining all lists)

• [ ] Improve make_newick() to make it recursive

• [ ] Improve the shiny application version

• [x] Redo pass_info function to only infer unknown values and only from the value of direct ancestors

• [x] Implement popups and labels for markers

• [ ] Implement popups and labels for polylines

• [x] Black background on leaflet

• [x] Repair the size legend

• [x] Option to thicker the line depending on a variable

• [x] Improve create_matrix function to pass check

How to use during development

Go to the package's folder

require(devtools)
devtools::load_all()

then you can simply use the package's functions.