{"id":26123,"date":"2024-01-24T17:28:59","date_gmt":"2024-01-24T09:28:59","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26123"},"modified":"2024-01-24T17:29:00","modified_gmt":"2024-01-24T09:29:00","slug":"%e4%b8%89%e5%88%86%e9%92%9f%e7%bb%98%e5%88%b6%e5%8f%8c%e6%9b%b2%e7%ba%bf%e6%96%b0%e5%9e%8b%e7%81%ab%e5%b1%b1%e5%9b%be-%e5%8f%8c%e6%9b%b2%e7%ba%bf%e7%81%ab%e5%b1%b1%e5%9b%be","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26123","title":{"rendered":"\u4e09\u5206\u949f\u7ed8\u5236\u53cc\u66f2\u7ebf\u65b0\u578b\u706b\u5c71\u56fe-\u53cc\u66f2\u7ebf\u706b\u5c71\u56fe"},"content":{"rendered":"

\u6700\u8fd1\u5728\u5f88\u591a\u7684\u6587\u7ae0\u4e2d\u51fa\u73b0\u4e86\u4e0b\u56fe\u7c7b\u4f3c\u7684\u65b0\u578b\u706b\u5c71\u56fe\uff0c\u5176\u5b9e\u539f\u7406\u5c31\u662f\uff0c\u5206\u522b\u4ee5\u539f\u6765\u7684\u7684\u9608\u503c\u7ebf\u4e3a\u57fa\u51c6\uff0c\u753b\u4e24\u4e2a\u539f\u59cb\u51fd\u6570\u4e3ay=1\/x\u7684\u7684\u66f2\u7ebf\u3002\u8fd9\u6837\u5bf9\u57fa\u56e0\u8fdb\u884c\u5206\u7c7b\uff0c\u6709\u5229\u4e8e\u7b5b\u9009\u5dee\u5f02\u66f4\u663e\u8457\u7684\u57fa\u56e0\u3002\u56e0\u6b64\u56fe\u5f62\u4e5f\u53d8\u7684\u7f8e\u89c2\u3002<\/p>\n

\"IMG_256\"<\/p>\n

\u5b89\u88c5\u76f8\u5e94\u7684\u5305\u5e76\u52a0\u8f7d<\/h2>\n

#\u76f8\u5173R\u5305\u8f7d\u5165\uff1a<\/p>\n

library(dplyr)<\/p>\n

library(ggplot2)<\/p>\n

library(ggrepel)<\/p>\n

library(patchwork)<\/p>\n

#\u672c\u5730\u6d4b\u8bd5\u6570\u636e\u8bfb\u5165\uff0c\u5177\u4f53\u6570\u636e\u89c1\u9644\u4ef6<\/p>\n

df <- read.csv(‘.\/test.xls’,header = T,sep = “\\t”)<\/p>\n

head(df)<\/p>\n

##\u7b5b\u9009\u9608\u503c\u786e\u5b9a\uff0c\u4e00\u822c\u9608\u503c\u662fp\uff1c0.05\uff0c|log2FC|\uff1e1<\/p>\n

pvalue = 0.05<\/p>\n

log2FC = 1<\/p>\n

#\u6839\u636e\u9608\u503c\u6dfb\u52a0\u4e0a\u4e0b\u8c03\u5206\u7ec4\u6807\u7b7e\uff1a<\/p>\n

df$group <- case_when(<\/p>\n

df$log2FC > log2FC & df$Pvalue < pvalue ~ “up”,<\/p>\n

df$log2FC < -log2FC & df$Pvalue < pvalue ~ “down”,<\/p>\n

TRUE ~ ‘none’<\/p>\n

)<\/p>\n

head(df)<\/p>\n

#\u8f6c\u6362\u4e3a\u56e0\u5b50\u6307\u5b9a\u7ed8\u56fe\u987a\u5e8f\uff1b<\/p>\n

df$’-log10(pvalue)’ <- -log10(df$Pvalue) #\u65b0\u589e-log10p\u5217<\/p>\n

df$group <- factor(df$group, levels = c(“up”,”down”,”none”))<\/p>\n

#ggplot2\u5efa\u7acb\u6620\u5c04\uff1a<\/p>\n

p <- ggplot(data = df,<\/p>\n

aes(x = log2FC, y = `-log10(pvalue)`, color = group)) + #\u5efa\u7acb\u6620\u5c04<\/p>\n

geom_point(size = 2.2) #\u7ed8\u5236\u6563\u70b9<\/p>\n

p<\/p>\n

\"\u622a\u5c4f2023-07-25<\/p>\n

#\u6839\u636e\u81ea\u5df1\u7684\u9700\u6c42\u53ef\u4ee5\u8c03\u6574\u4e0b\u5217\u53c2\u6570\uff0c\u8fdb\u884c\u7ed8\u56fe\u3002<\/p>\n

p1 <- p +<\/p>\n

scale_x_continuous(limits = c(-7, 7), breaks = seq(-7, 7, by = 2))+<\/p>\n

scale_y_continuous(expand = expansion(add = c(0.5, 0)),<\/p>\n

limits = c(0, 10), breaks = seq(0, 10, by = 5))<\/p>\n

p1<\/p>\n

\"\u622a\u5c4f2023-07-25<\/p>\n

#\u81ea\u5b9a\u4e49\u989c\u8272\u4e0e\u4e3b\u9898\uff1a<\/p>\n

mycol <- c(“#EB4232″,”#2DB2EB”,”#d8d8d8″)<\/p>\n

mytheme <- theme_classic() +<\/p>\n

theme(<\/p>\n

axis.title = element_text(size = 15),<\/p>\n

axis.text = element_text(size = 14),<\/p>\n

legend.text = element_text(size = 14)<\/p>\n

)<\/p>\n

p2 <- p1 +<\/p>\n

scale_colour_manual(name = “”, values = alpha(mycol, 0.7)) +<\/p>\n

mytheme<\/p>\n

p2<\/p>\n

\"\u622a\u5c4f2023-07-25<\/p>\n

#\u6dfb\u52a0\u9608\u503c\u8f85\u52a9\u7ebf<\/p>\n

p3 <- p2 +<\/p>\n

geom_hline(yintercept = c(-log10(pvalue)),size = 0.7,color = “black”,lty = “dashed”) + #\u6c34\u5e73\u9608\u503c\u7ebf<\/p>\n

geom_vline(xintercept = c(-log2FC, log2FC),size = 0.7,color = “black”,lty = “dashed”) #\u5782\u76f4\u9608\u503c\u7ebf<\/p>\n

p3<\/p>\n

\"\u622a\u5c4f2023-07-25<\/p>\n

\u6dfb\u52a0\u53cc\u66f2\u7ebf<\/h2>\n

#\u6839\u636e\u53cd\u6bd4\u4f8b\u51fd\u6570 y = 1\/X\u548c\u81ea\u5df1\u8bbe\u5b9a\u7684\u9608\u503c\u81ea\u5b9a\u4e49\u53cc\u66f2\u7ebf\u51fd\u6570<\/p>\n

f <- function(x){<\/p>\n

inputx <- seq(0.0001, x, by = 0.0001)<\/p>\n

y <- 1\/(inputx) + (-log10(pvalue))<\/p>\n

dff <- rbind(data.frame(x = inputx + log2FC, y = y),<\/p>\n

data.frame(x = -(inputx + log2FC), y = y))<\/p>\n

return(dff)<\/p>\n

}<\/p>\n

#\u6839\u636e\u51fd\u6570\u751f\u6210\u6240\u9700\u7684\u66f2\u7ebf\u6570\u7ec4\u5750\u6807\uff1a<\/p>\n

dff_curve <- f(2)<\/p>\n

head(dff_curve)<\/p>\n

#\u9700\u8981\u65b0\u589e\u66f2\u7ebf\u6570\u503c\u5217\uff1a<\/p>\n

##\u6bcf\u5217log2FoldChange\u503c\u5728\u66f2\u7ebf\u4e0a\u5bf9\u5e94\u7684y\u8f74\u5750\u6807\uff1b<\/p>\n

df$curve_y <- case_when(<\/p>\n

df$log2FC > 0 ~ 1\/(df$log2FC-log2FC) + (-log10(pvalue)),<\/p>\n

df$log2FC <= 0 ~ 1\/(-df$log2FC-log2FC) + (-log10(pvalue))<\/p>\n

)<\/p>\n

#\u8ddf\u524d\u6587\u8bb2\u8ff0\u7684\u4e00\u6837\u6839\u636e\u66f2\u7ebf\u65b0\u589e\u4e0a\u4e0b\u8c03\u5206\u7ec4\u6807\u7b7e\uff1a<\/p>\n

df$group2 <- case_when(<\/p>\n

df$`-log10(pvalue)` > df$curve_y & df$log2FC >= log2FC ~ ‘up’,<\/p>\n

df$`-log10(pvalue)` > df$curve_y & df$log2FC <= -log2FC ~ ‘down’,<\/p>\n

TRUE ~ ‘none’<\/p>\n

)<\/p>\n

#\u7ed8\u5236\u65b0\u53cc\u66f2\u7ebf\u9608\u503c\u706b\u5c71\u56fe\uff1a<\/p>\n

df$group2 <- factor(df$group2, levels = c(“up”,”down”,”none”)) #\u6307\u5b9a\u987a\u5e8f<\/p>\n

mycol2 <- c(“#F8B606″,”#4A1985″,”#d8d8d8”)<\/p>\n

p4 <- ggplot(data = df,<\/p>\n

aes(x = log2FC, y = `-log10(pvalue)`, color = group2)) + #\u4f7f\u7528\u65b0\u7684\u5206\u7ec4<\/p>\n

geom_point(size = 2.2) +<\/p>\n

scale_x_continuous(limits = c(-7, 7), breaks = seq(-7, 7, by = 2)) +<\/p>\n

scale_y_continuous(expand = expansion(add = c(0.5, 0)),<\/p>\n

limits = c(0, 10), breaks = seq(0, 10, by = 5)) +<\/p>\n

scale_colour_manual(name = “”, values = alpha(mycol2, 0.7)) +<\/p>\n

geom_line(data = dff_curve,<\/p>\n

aes(x = x, y = y), #\u66f2\u7ebf\u5750\u6807<\/p>\n

color = “black”,lty = “dashed”, size = 0.7) +<\/p>\n

mytheme<\/p>\n

p4<\/p>\n

\"\u622a\u5c4f2023-07-25<\/p>\n

\u6dfb\u52a0\u6807\u7b7e<\/h2>\n

#\u7b5b\u9009\u663e\u8457\u6027top10\u6807\u7b7e\uff1a<\/p>\n

top10 <- filter(df, group2 != “none”) %>%<\/p>\n

distinct(GeneName, .keep_all = T) %>%<\/p>\n

top_n(10, abs(log2FC))<\/p>\n

p5 <- p4 +<\/p>\n

geom_text_repel(data = top10,<\/p>\n

aes(x = log2FC, y = `-log10(pvalue)`, label = GeneName),<\/p>\n

force = 80, color = ‘black’, size = 3.2,<\/p>\n

point.padding = 0.5, hjust = 0.5,<\/p>\n

arrow = arrow(length = unit(0.02, “npc”),<\/p>\n

type = “open”, ends = “last”),<\/p>\n

segment.color=”black”,<\/p>\n

segment.size = 0.3,<\/p>\n

nudge_x = 0,<\/p>\n

nudge_y = 1)<\/p>\n

p5<\/p>\n

\"\u622a\u5c4f2023-07-25<\/p>\n

\u8865\u5145\u5173\u4e8e\u706b\u5c71\u56fe\u5dee\u5f02\u7b5b\u9009\u7684\u7edf\u8ba1\u5b66\u610f\u4e49\uff1a<\/p>\n

1\u3001\u4ec0\u4e48\u662ffold change?<\/p>\n

\u5dee\u5f02\u500d\u6570\uff0c\u7b80\u5355\u6765\u8bf4\u5c31\u662f\u57fa\u56e0\u5728\u4e00\u7ec4\u6837\u54c1\u4e2d\u7684\u8868\u8fbe\u503c\u7684\u5747\u503c\u9664\u4ee5\u5176\u5728\u53e6\u4e00\u7ec4\u6837\u54c1\u4e2d\u7684\u8868\u8fbe\u503c\u7684\u5747\u503c\u3002\u6240\u4ee5\u706b\u5c71\u56fe\u53ea\u9002\u5408\u5c55\u793a\u4e24\u7ec4\u6837\u54c1\u4e4b\u95f4\u7684\u6bd4\u8f83\u3002<\/p>\n

2\u3001\u4e3a\u4ec0\u4e48\u8981\u505aLog 2\u8f6c\u6362\uff1f<\/p>\n

\u7ed8\u5236\u5230\u56fe\u4e2d\u65f6\uff0c\u4e0a\u8c03\u5360\u7684\u7a7a\u95f4\u591a\uff0c\u4e0b\u8c03\u5360\u7684\u7a7a\u95f4\u5c11\uff0c\u5c55\u793a\u8d77\u6765\u4e0d\u65b9\u4fbf\u3002\u6240\u4ee5\u4e00\u822c\u4f1a\u505aLog 2\u8f6c\u6362\u3002\u9ed8\u8ba4\u6211\u4eec\u90fd\u4f1a\u7528\u4e24\u500d\u5dee\u5f02 \uff08fold change == 2 | 0.5\uff09\u505a\u4e3a\u4e00\u4e2a\u7b5b\u9009\u6807\u51c6\u3002<\/p>\n

3\u3001P-value\u90fd\u6bd4\u8f83\u719f\u6089\uff0c\u7edf\u8ba1\u68c0\u9a8c\u83b7\u5f97\u7684\u662f\u5426\u7edf\u8ba1\u5dee\u5f02\u663e\u8457\u7684\u4e00\u4e2a\u8861\u91cf\u503c\uff0c\u7ea6\u5b9a\u6210\u4fd7\u7684P-value<0.05\u4e3a\u7edf\u8ba1\u68c0\u9a8c\u663e\u8457\u7684\u5e38\u89c4\u6807\u51c6\u3002<\/p>\n

4\u3001\u4ec0\u4e48\u662fadjusted P-value?<\/p>\n

\u505a\u5dee\u5f02\u57fa\u56e0\u68c0\u6d4b\u65f6\uff0c\u8981\u5bf9\u6210\u5343\u4e0a\u4e07\u7684\u57fa\u56e0\u5206\u522b\u505a\u5dee\u5f02\u7edf\u8ba1\u68c0\u9a8c\u3002\u7edf\u8ba1\u5b66\u5bb6\u8ba4\u4e3a\u505a\u8fd9\u4e48\u591a\u6b21\u7684\u68c0\u9a8c\uff0c\u672c\u8eab\u5c31\u4f1a\u5f15\u5165\u5047\u9633\u6027\u7ed3\u679c\uff0c\u9700\u8981\u505a\u4e00\u4e2a\u591a\u91cd\u5047\u8bbe\u68c0\u9a8c\u6821\u6b63\u3002<\/p>\n

5\u3001\u4e3a\u4ec0\u4e48\u505a-Log 10\u8f6c\u6362\u5462\uff1f<\/p>\n

\u56e0\u4e3aFDR\u503c\u662f0-1\u4e4b\u95f4\uff0c\u6570\u503c\u8d8a\u5c0f\u8d8a\u662f\u7edf\u8ba1\u663e\u8457\uff0c\u4e5f\u8d8a\u662f\u6211\u4eec\u5173\u6ce8\u7684\u3002-Log 10 (adjusted P-value)\u8f6c\u6362\u540e\u6b63\u597d\u662f\u53cd\u4e86\u591a\u6765\uff0c\u6570\u503c\u8d8a\u5927\u8d8a\u663e\u8457\uff0c\u800c\u4e14\u4ee510\u4e3a\u5e95\u5f88\u5bb9\u6613\u6362\u7b97\u56de\u53bb\u3002<\/p>\n

\u5982\u679c\u9047\u5230\u4e0d\u61c2\u7684\u4e5f\u53ef\u4ee5\u501f\u52a9\u7ebf\u4e0a\u7684\u4e91\u5e73\u53f0\u54e6\uff5ehttp:\/\/www.biocloudservice.com\/home.html<\/p>\n

\u597d\u4e86\u4eca\u5929\u7684\u706b\u5c71\u56fe\u5c31\u8bb2\u5230\u8fd9\u91cc\uff0c\u6b22\u8fce\u5927\u5bb6\u6709\u95ee\u9898\u4e0e\u5c0f\u679c\u4e00\u8d77\u8ba8\u8bba\u54e6\uff5e<\/p>\n","protected":false},"excerpt":{"rendered":"

\u6700\u8fd1\u5728\u5f88\u591a\u7684\u6587\u7ae0\u4e2d\u51fa\u73b0\u4e86\u4e0b\u56fe\u7c7b\u4f3c\u7684\u65b0\u578b\u706b\u5c71\u56fe\uff0c\u5176\u5b9e\u539f\u7406\u5c31\u662f\uff0c\u5206\u522b\u4ee5\u539f\u6765\u7684\u7684\u9608\u503c\u7ebf\u4e3a\u57fa\u51c6\uff0c\u753b\u4e24\u4e2a\u539f\u59cb\u51fd\u6570\u4e3ay=1 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":""},"categories":[1],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26123"}],"collection":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=26123"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26123\/revisions"}],"predecessor-version":[{"id":26131,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26123\/revisions\/26131"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=26123"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=26123"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=26123"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}