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R包:ggsci期刊配色

R包:ggsci期刊配色

作者: 生信学习者2 | 来源:发表于2021-11-19 09:39 被阅读0次

    介绍

    不同期刊配色大多数时候不一样,为了更好符合期刊图片颜色的配色,有人开发了ggsci这个R包。它提供以下函数:

    • scale_color_palname()

    • scale_fill_palname()

    对应不同期刊的color和fill函数。

    导入数据+R包

    library("ggsci")
    library("ggplot2")
    library("gridExtra")
    
    data("diamonds")
    
    p1 <- ggplot(subset(diamonds, carat >= 2.2),
           aes(x = table, y = price, colour = cut)) +
           geom_point(alpha = 0.7) +
          geom_smooth(method = "loess", alpha = 0.05, size = 1, span = 1) +
          theme_bw()
    
    p2 <-  ggplot(subset(diamonds, carat > 2.2 & depth > 55 & depth < 70),
              aes(x = depth, fill = cut)) +
              geom_histogram(colour = "black", binwidth = 1, position = "dodge") +
              theme_bw()
    

    NPG: Nature Publishing Group

    p1_npg <- p1 + scale_color_npg()
    p2_npg <- p2 + scale_fill_npg()
    grid.arrange(p1_npg, p2_npg, ncol = 2)
    

    AAAS: American Association for the Advancement of Science

    p1_aaas <- p1 + scale_color_aaas()
    p2_aaas <- p2 + scale_fill_aaas()
    grid.arrange(p1_aaas, p2_aaas, ncol = 2)
    

    NEJM:The New England Journal of Medicine

    p1_nejm <- p1 + scale_color_nejm()
    p2_nejm <- p2 + scale_fill_nejm()
    grid.arrange(p1_nejm, p2_nejm, ncol = 2)
    

    Lancet: Lancet journals

    p1_lancet <- p1 + scale_color_lancet()
    p2_lancet <- p2 + scale_fill_lancet()
    grid.arrange(p1_lancet, p2_lancet, ncol = 2)
    

    JAMA: The Journal of the American Medical Association

    p1_jama <- p1 + scale_color_jama()
    p2_jama <- p2 + scale_fill_jama()
    grid.arrange(p1_jama, p2_jama, ncol = 2)
    

    UCSCGB: UCSC Genome Browser

    p1_ucscgb <- p1 + scale_color_ucscgb()
    p2_ucscgb <- p2 + scale_fill_ucscgb()
    grid.arrange(p1_ucscgb, p2_ucscgb, ncol = 2)
    

    Tron Legacy

    p1_tron <- p1 + theme_dark() + theme(
        panel.background = element_rect(fill = "#2D2D2D"),
        legend.key = element_rect(fill = "#2D2D2D")) +
      scale_color_tron()
    p2_tron <- p2 + theme_dark() + theme(
        panel.background = element_rect(fill = "#2D2D2D")) +
      scale_fill_tron()
    grid.arrange(p1_tron, p2_tron, ncol = 2)
    

    GSEA: GSEA GenePattern

    library("reshape2")
    
    data("mtcars")
    cor <- cor(unname(cbind(mtcars, mtcars, mtcars, mtcars)))
    cor_melt <- melt(cor)
    
    p3 <- ggplot(cor_melt, aes(x = Var1, y = Var2, fill = value)) +
      geom_tile(colour = "black", size = 0.3) +
      theme_bw() +
      theme(axis.title.x = element_blank(),
            axis.title.y = element_blank())
    
    p3_gsea <- p3 + scale_fill_gsea()
    p3_gsea_inv <- p3 + scale_fill_gsea(reverse = TRUE)
    grid.arrange(p3_gsea, p3_gsea_inv, ncol = 2)
    

    Reference

    1. ggsci

    参考文章如引起任何侵权问题,可以与我联系,谢谢。

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