下面是一个使用geom_tile()的解决方案，
1.我们为背景颜色创建一个数据框
1.当我们使用geom_tile()时，我们将设置x美学，以覆盖图的整个宽度，并相应地调整每个图块的宽度。

1. geom_tile()使用x = sum(x_limits) / 2将切片定位在图的中心，使用width = diff(x_limits)确保每个切片跨越图的整个宽度

library(ggplot2)
library(dplyr)

set.seed(123)
plot_df <- data.frame(
  gene = rep(paste0("ENSG", 1:10, ".17"), each = 2),
  mean = rnorm(20, 0.5, 0.1),
  sd = rnorm(20, 0.02, 0.01),
  group = rep(c("group_a", "group_b"), 10)
)

# df for background colors
bg_df <- plot_df %>%
  distinct(gene) %>%
  arrange(gene) %>% 
  mutate(color = ifelse(row_number() %% 2 == 1, "gold", "lightgrey"))

# x axis limts based on data 
x_limits <- range(plot_df$mean - plot_df$sd, plot_df$mean + plot_df$sd, na.rm = TRUE)

# the plot
ggplot(plot_df, aes(y = gene, x = mean)) +
  geom_tile(data = bg_df, aes(y = gene, x = sum(x_limits) / 2, width = diff(x_limits), fill = color), 
            alpha = 0.3, inherit.aes = FALSE) +
  geom_point(aes(color = group), position = position_dodge(width = 0.9)) +
  geom_errorbar(aes(xmin = mean - sd, xmax = mean + sd, color = group), 
                width = 0.2, position = position_dodge(.9)) +
  scale_color_manual(values = c("steelblue3", "red3"))+
  geom_vline(xintercept = 0.5, linetype = 2, color = 'gray80') +
  theme_bw() +
  theme(panel.background = element_blank(),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        legend.position = "right") +
  scale_fill_identity()

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另一种选择是使用geom_rect，将离散的gene s转换为数字，并为ymin/ymax添加-/+.5。此外，将xmin/max设置为-/+Inf可以填充整个面板，其中我还将y尺度的扩展减少到.5。
请注意，我们必须显式调用scale_y_discrete()来强制离散缩放，因为我添加了geom_rect作为第一层（否则会出现错误，因为ggplot2将默认为连续缩放）。此外，我为rect使用单独的矩形，以避免为每个group添加矩形，而不是每个gene只添加一个矩形。

library(ggplot2)
library(dplyr)

set.seed(123)
plot_df <- data.frame(
  gene = rep(paste0("ENSG", 1:10, ".17"), each = 2),
  mean = rnorm(20, 0.5, 0.1),
  sd = rnorm(20, 0.02, 0.01),
  group = rep(c("group_a", "group_b"), 10)
)

rect_df <- plot_df |>
  distinct(gene) |> 
  mutate(
    ymin = as.numeric(factor(gene)) - .5,
    ymax = as.numeric(factor(gene)) + .5,
    fill = factor(as.numeric(factor(gene)) %% 2)
  )

# the plot
ggplot(plot_df, aes(y = gene)) +
  geom_rect(
    data = rect_df,
    aes(ymin = ymin, ymax = ymax, fill = fill, xmin = -Inf, xmax = Inf),
    alpha = .3
  ) +
  geom_point(aes(x = mean, color = group),
    position = position_dodge(width = 0.9)
  ) +
  geom_errorbar(aes(xmin = mean - sd, xmax = mean + sd, color = group),
    width = .2,
    position = position_dodge(.9)
  ) +
  geom_vline(aes(xintercept = 0.5), linetype = 2, color = "gray") +
  scale_y_discrete(expand = c(0, .5)) +
  scale_fill_manual(values = c("grey90", "grey60"), guide = "none") +
  theme_bw() +
  theme(
    panel.background = element_blank(),
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank()
  )

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