Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression R….

hidecan

hidecan is an R package for generating HIDECAN plots, which are visualisations summarising the results of one or more Genome-wide association study (GWAS) and transcriptomics differential expression (DE) analysis, alongside candidate genes of interest.

Installation

You can install the development version of hidecan from GitHub with:

# install.packages("devtools")
devtools::install_github("PlantandFoodResearch/hidecan")

Usage

The hidecan package works as follows:

• it takes as an input one of more data-frames containing GWAS results, differential expression results and list of candidate genes of interest;

• it computes the length of each chromosome based on the genomic position of the markers and genes provided in the input data;

• it filters the datasets to retain significant markers or differentially expressed genes, according to a threshold on their score and/or log2-fold change. The fold-change is set by the user, and can be different for GWAS and differential expression results.

• it displays the position of the significant markers and genes alongside candidate genes (HIDECAN plot). The plot can be customised by the user via a number of parameters (e.g. legend position or label size).

The wrapper function hidecan_plot() performs all of these steps. Its use is demonstrated below with an example dataset:

library(hidecan)

## Getting an example dataset
x <- get_example_data()

hidecan_plot(
  gwas_list = x[["GWAS"]],          ## data-frame of GWAS results
  de_list = x[["DE"]],              ## data-frame of DE results
  can_list = x[["CAN"]],            ## data-frame of candidate genes
  score_thr_gwas = -log10(0.0001),  ## sign. threshold for GWAS
  score_thr_de = -log10(0.05),      ## sign. threshold for DE
  log2fc_thr = 0,                   ## log2FC threshold for DE
  label_size = 2                    ## label size for candidate genes
)