geneviewer (version 0.1.10)

GC_normalize: Normalize Gene Clusters in a Genomic Chart

Description

This function normalizes the genomic coordinates of a set of genes within a cluster, ensuring that the genes are evenly spaced along the entire range of the cluster. The function allows for the option to preserve the original gene lengths and to introduce customized gaps between the genes.

Usage

GC_normalize(
  GC_chart,
  group = NULL,
  cluster = NULL,
  normalize = TRUE,
  preserve_gene_length = TRUE,
  gap = NULL,
  custom_gaps = list()
)

Value

The modified `GC_chart` object with normalized gene coordinates for the specified clusters.

Arguments

GC_chart

A chart object containing genomic data and clustering information. The chart object must include a `series` component with data for each cluster.

group

Column name containing gene names to apply custom gaps to.

cluster

A vector of cluster names to be normalized. If `NULL`, all clusters in the `GC_chart` will be normalized.

normalize

A logical value indicating whether to normalize the gene positions within each cluster. Default is `TRUE`.

preserve_gene_length

A logical vector indicating whether to preserve the original gene lengths for each cluster. If a single value is provided, it is recycled for all clusters.

gap

A numeric vector specifying the proportion of the total length to be used as the gap between genes in each cluster. The value must be between 0 and 1. If a single value is provided, it is recycled for all clusters. If `NULL`, the gaps are calculated based on the actual spacing between the genes in the original data.

custom_gaps

A named list where each name corresponds to a gene name and each value is a numeric factor by which to adjust the gap after that gene.

Examples

genes_data <- data.frame(
  start = c(10, 90, 130, 10, 90, 130),
  end = c(40, 120, 160, 40, 120, 160),
  name = c('Gene 1', 'Gene 2', 'Gene 3','Gene 1', 'Gene 2', 'Gene 3'),
  group = c('A', 'B', 'C', 'A', 'B', 'C'),
  cluster =  c(1, 1, 1, 2, 2, 2)
)

GC_chart(genes_data, group = "group", cluster = "cluster", height = "150px") %>%
  GC_normalize(
    cluster = 2,
    preserve_gene_length = TRUE,
    gap = NULL
 )