PCA_plot.rtf

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\f0\fs24 \cf0 ### PCA plot function ###\
PCA_plot <- function(m, groups, samplenames, batch, legend_colors, plot_path=NULL)\{\
  \
  # load package\
  library(ggplot2)\
  library(plotly)\
\
  # replace NAs with 0\
  m[is.na(m)] <- 0\
  \
  # calculate PCA\
  pca_res <- prcomp(t(m))\
  rot_mat <- pca_res$rotation\
  res_final <- as.matrix(scale(t(m), center=TRUE, scale=FALSE)) %*% rot_mat\
  eigenvectors <- pca_res$sdev^2\
  anteil_var_pca1 <- round(eigenvectors[1]/sum(eigenvectors),digits=3)\
  anteil_var_pca2 <- round(eigenvectors[2]/sum(eigenvectors),digits=3)\
  \
  ## create groups\
  groups <- factor(groups, levels=names(legend_colors))\
  colors <- legend_colors\
  names(colors) <- levels(groups)\
  colors <- colors[names(colors) %in% groups]\
  \
  ## ggplot PCR\
  if(is.null(batch))\{\
    df_gg <- as.data.frame(res_final)\
    df_gg$samplenames <- samplenames\
    df_gg$groups <- groups\
    gg <- ggplot(df_gg) + \
      geom_point(aes(x=PC1, y=PC2, col=groups, text=samplenames),size=5) +\
      scale_color_manual(values=colors)+\
      xlab(paste0("PC1  ","(",anteil_var_pca1*100,"%",")")) +\
      ylab(paste0("PC2  ","(",anteil_var_pca2*100,"%",")")) +\
      theme_bw()\
  \} else \{\
    df_gg <- as.data.frame(res_final)\
    df_gg$samplenames <- samplenames\
    df_gg$groups <- groups\
    df_gg$batch <- as.factor(batch)\
    gg <- ggplot(df_gg) + \
      geom_point(aes(x=PC1, y=PC2, col=groups, text=samplenames, shape=batch),size=5) +\
      scale_color_manual(values=colors)+\
      xlab(paste0("PC1  ","(",anteil_var_pca1*100,"%",")")) +\
      ylab(paste0("PC2  ","(",anteil_var_pca2*100,"%",")")) +\
      theme_bw()\
  \}\
  \
  # save plot\
  if(!is.null(plot_path))\{\
    ggsave(plot=gg, filename=plot_path, width = 6, height = 4)\
  \}\
  \
  # print plot\
  ggplotly(gg)\
\}}