Hello I am trying to plot confidence interval in a Gviz plot without having this kind of connected effect always displayed by GViz

(see example below) is there a simple way to get this kind of confidence interval plotted in a base pair fashion?

# Load required libraries
library(GViz)
library(GenomicRanges)

# Example data: Genetic positions, point estimates, and confidence intervals
data <- data.frame(
  chromosome = "chr1",  # Modify for different chromosomes
  position = c(100000, 200000, 300000, 400000, 500000),  # Base pair positions
  estimate = c(0.2, -0.3, 0.5, -0.1, 0.4),  # Point estimates
  ci_width = c(0.05, 0.1, 0.08, 0.06, 0.09)  # Half-width of confidence intervals
)

# Compute confidence interval bounds
data$ci_lower <- data$estimate - data$ci_width
data$ci_upper <- data$estimate + data$ci_width

# Create GenomicRanges objects
gr_points <- GRanges(seqnames = data$chromosome, 
                     ranges = IRanges(start = data$position, end = data$position),
                     estimate = data$estimate)

gr_ci <- GRanges(seqnames = data$chromosome, 
                 ranges = IRanges(start = data$position, end = data$position),
                 ci_lower = data$ci_lower,
                 ci_upper = data$ci_upper)

# DataTrack for point estimates (scatter plot)
points_track <- DataTrack(gr_points, 
                          name = "Effect Sizes",
                          type = "p",  # 'p' for points
                          col = "blue",
                          cex = 1.5,  # Point size
                          pch = 19)  # Solid circles

# DataTrack for confidence intervals (lines)
ci_track <- DataTrack(gr_ci, 
                      name = "Confidence Intervals",
                      type = "line",  # 'line' for error bars
                      col = "black",
                      lwd = 2,  # Line width
                      from = data$ci_lower,  # Lower bound
                      to = data$ci_upper)  # Upper bound

# Genome axis track for better visualization
gtrack <- GenomeAxisTrack()

# Chromosome ideogram track (Optional, requires BSgenome package)
itrack <- IdeogramTrack(genome = "hg19", chromosome = "chr1")

# Plot the GViz tracks
plotTracks(list(itrack, gtrack, ci_track, points_track), 
           from = min(data$position) - 50000, 
           to = max(data$position) + 50000,
           main = "Effect Sizes with Confidence Intervals")