Nothing
callModule(server.home_search_box, "homepage_pancan_search")
output$Xenasummary1 <- plotly::renderPlotly({
p <- Xena_summary %>%
ggplot(aes(x = Hub, y = n_cohort, fill = Hub)) +
ggplot2::geom_bar(stat = "identity", width = 0.8) +
ggplot2::coord_flip() +
ggplot2::labs(x = NULL, y = NULL) +
ggplot2::theme_bw(base_size = 15) + # 去除背景色
ggplot2::theme(panel.grid = ggplot2::element_blank()) + # 去除网格线
ggplot2::theme(panel.border = ggplot2::element_blank()) + # 去除外层边框
ggplot2::theme(axis.line = ggplot2::element_line(colour = "black")) + # 沿坐标轴显示直线
ggplot2::guides(fill = "none") +
ggplot2::guides(color = "none") +
ggplot2::scale_fill_manual(values = mycolor)
plotly::ggplotly(p) %>% plotly::layout(showlegend = FALSE)
})
output$Xenasummary2 <- plotly::renderPlotly({
p <- Xena_summary %>%
ggplot(aes(x = Hub, y = n_dataset, fill = Hub)) +
ggplot2::geom_bar(stat = "identity", width = 0.8) +
ggplot2::coord_flip() +
ggplot2::labs(x = NULL, y = NULL) +
ggplot2::theme_bw(base_size = 15) + # 去除背景色
ggplot2::theme(panel.grid = ggplot2::element_blank()) + # 去除网格线
ggplot2::theme(panel.border = ggplot2::element_blank()) + # 去除外层边框
ggplot2::theme(axis.line = ggplot2::element_line(colour = "black")) + # 沿坐标轴显示直线
ggplot2::guides(fill = FALSE) +
ggplot2::guides(color = FALSE) +
ggplot2::scale_fill_manual(values = mycolor)
plotly::ggplotly(p) %>% plotly::layout(showlegend = FALSE)
})
# output$Xenasummary <- plotly::renderPlotly({
# p <- dat_datasets %>%
# # filter(XenaHostNames == "gdcHub") %>%
# dplyr::rename(
# Hub = XenaHostNames, Percent = Sample_percent,
# Cohort = XenaCohorts, DatasetCount = N
# ) %>%
# ggplot2::ggplot(ggplot2::aes(x = Hub, y = Percent, fill = Cohort, label = DatasetCount)) +
# ggplot2::geom_bar(stat = "identity", width = 0.8, color = "black") +
# ggplot2::coord_flip() +
# ggplot2::labs(y = "", x = "") +
# ggplot2::theme_bw(base_size = 15) + # 去除背景色
# ggplot2::theme(panel.grid = ggplot2::element_blank()) + # 去除网格线
# ggplot2::theme(panel.border = ggplot2::element_blank()) + # 去除外层边框
# ggplot2::theme(axis.line = ggplot2::element_line(colour = "black")) + # 沿坐标轴显示直线
# ggplot2::theme(
# axis.line.x = ggplot2::element_blank(),
# axis.ticks.x = ggplot2::element_blank(),
# axis.text.x = ggplot2::element_blank()
# ) + # 去除x轴
# ggplot2::guides(fill = F) +
# ggplot2::guides(color = F) +
# ggplot2::scale_fill_manual(values = mycolor)
#
# plotly::ggplotly(p, tooltip = c("fill", "label")) %>% plotly::layout(showlegend = FALSE)
# })
# output$Xenasummary1 <- plotly::renderPlotly({
# p <- dat_samples %>%
# # filter(XenaHostNames == "gdcHub") %>%
# dplyr::rename(
# Hub = XenaHostNames, Percent = SampleCount_percent,
# Cohort = XenaCohorts, SampleCount = SampleCount_sum
# ) %>%
# ggplot2::ggplot(ggplot2::aes(x = Hub, y = Percent, fill = Cohort, label = SampleCount)) +
# ggplot2::geom_bar(stat = "identity", width = 0.8, color = "black") +
# ggplot2::coord_flip() +
# ggplot2::labs(y = "", x = "") +
# ggplot2::theme_bw(base_size = 15) + # 去除背景色
# ggplot2::theme(panel.grid = ggplot2::element_blank()) + # 去除网格线
# ggplot2::theme(panel.border = ggplot2::element_blank()) + # 去除外层边框
# ggplot2::theme(axis.line = ggplot2::element_line(colour = "black")) + # 沿坐标轴显示直线
# ggplot2::theme(
# axis.line.x = ggplot2::element_blank(),
# axis.ticks.x = ggplot2::element_blank(),
# axis.text.x = ggplot2::element_blank()
# ) + # 去除x轴
# ggplot2::guides(fill = F) +
# ggplot2::guides(color = F) +
# ggplot2::scale_fill_manual(values = mycolor)
# plotly::ggplotly(p, tooltip = c("fill", "label")) %>% plotly::layout(showlegend = FALSE)
# })
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