Differentially expression from depression RNA-seq

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

x <- read.csv("n-c.csv")
head(x)
##       X         gene_id Symbol      logFC   logCPM        F   PValue
## 1 12322 ENSG00000167716  WDR81 -0.5983161 4.312923 79.92917 9.88e-13
## 2   502 ENSG00000032444 PNPLA6 -0.5028262 6.102135 70.86831 7.78e-12
## 3  8206 ENSG00000141456  PELP1 -0.5030230 5.227286 58.92551 1.49e-10
## 4  2253 ENSG00000100241   SBF1 -0.5080147 7.880080 57.34979 2.25e-10
## 5  8275 ENSG00000141959   PFKL -0.3409586 6.891222 55.87729 3.33e-10
## 6 11559 ENSG00000164713   BRI3 -0.4508838 3.508642 55.33628 3.85e-10
##        FDR label X.LogadjPValue expression
## 1 1.96e-08             7.707489         NA
## 2 7.73e-08             7.112038         NA
## 3 9.88e-07             6.005412         NA
## 4 1.12e-06             5.951412         NA
## 5 1.27e-06             5.895254         NA
## 6 1.27e-06             5.895254         NA
x$expression = ifelse(x$FDR < 0.05 & abs(x$logFC) >= 1, 
                     ifelse(x$logFC> 1 ,'Up','Down'),
                     'Stable')

Including Plots

You can also embed plots, for example:

library(ggplot2)
p <- ggplot(data = x, 
            aes(x = logFC, 
                y = -log10(x$FDR), 
                colour=expression,
                label = x$label)) +
  geom_point(alpha=0.4, size=3.5) +
  scale_color_manual(values=c("blue", "grey","red"))+
  xlim(c(-4.5, 4.5)) +
  geom_vline(xintercept=c(-1,1),lty=4,col="black",lwd=0.8) +
  geom_hline(yintercept = 1.301,lty=4,col="black",lwd=0.8) +
  labs(x="log2(fold change)",
       y="-log10 (adj.p-value)",
       title="Differential expression")  +
  theme_bw()+
  theme(plot.title = element_text(hjust = 0.5), 
        legend.position="right", 
        legend.title = element_blank())
p

library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
ggplotly(p)