引言

本系列 將開展全新的CUT&Tag 數據處理和分析專欄。想要獲取更多教程內容或者生信分析服務可以添加文末的學習交流群或客服QQ:941844452。

報告測序比對總結

對原始讀取和唯一比對讀取進行總結，以反映比對的效率。高質量數據的比對頻率通常應高于 80%。CUT&Tag 數據背景噪聲較低，因此在人類基因組中，僅需 100 萬比對片段就能為組蛋白修飾提供可靠的分析結果。而對于豐度較低的轉錄因子和染色質蛋白，下游分析可能需要 10 倍于該數量的比對片段。

我們可以評估以下指標：

• 測序深度
• 比對率
• 可比對片段數量
• 重復率
• 獨特文庫大小
• 片段大小分布

測序深度

##=== R command ===## 
## Path to the project and histone list
projPath = "/fh/fast/gottardo_r/yezheng_working/cuttag/CUTTag_tutorial"
sampleList = c("K27me3_rep1", "K27me3_rep2", "K4me3_rep1", "K4me3_rep2", "IgG_rep1", "IgG_rep2")
histList = c("K27me3", "K4me3", "IgG")

## Collect the alignment results from the bowtie2 alignment summary files
alignResult = c()
for(hist in sampleList){
  alignRes = read.table(paste0(projPath, "/alignment/sam/bowtie2_summary/", hist, "_bowtie2.txt"), header = FALSE, fill = TRUE)
  alignRate = substr(alignRes$V1[6], 1, nchar(as.character(alignRes$V1[6]))-1)
  histInfo = strsplit(hist, "_")[[1]]
  alignResult = data.frame(Histone = histInfo[1], Replicate = histInfo[2], 
                           SequencingDepth = alignRes$V1[1] %>% as.character %>% as.numeric, 
                           MappedFragNum_hg38 = alignRes$V1[4] %>% as.character %>% as.numeric + alignRes$V1[5] %>% as.character %>% as.numeric, 
                           AlignmentRate_hg38 = alignRate %>% as.numeric)  %>% rbind(alignResult, .)
}
alignResult$Histone = factor(alignResult$Histone, levels = histList)
alignResult %>% mutate(AlignmentRate_hg38 = paste0(AlignmentRate_hg38, "%"))

Spike-in alignment

##=== R command ===## 
spikeAlign = c()
for(hist in sampleList){
  spikeRes = read.table(paste0(projPath, "/alignment/sam/bowtie2_summary/", hist, "_bowtie2_spikeIn.txt"), header = FALSE, fill = TRUE)
  alignRate = substr(spikeRes$V1[6], 1, nchar(as.character(spikeRes$V1[6]))-1)
  histInfo = strsplit(hist, "_")[[1]]
  spikeAlign = data.frame(Histone = histInfo[1], Replicate = histInfo[2], 
                          SequencingDepth = spikeRes$V1[1] %>% as.character %>% as.numeric, 
                          MappedFragNum_spikeIn = spikeRes$V1[4] %>% as.character %>% as.numeric + spikeRes$V1[5] %>% as.character %>% as.numeric, 
                          AlignmentRate_spikeIn = alignRate %>% as.numeric)  %>% rbind(spikeAlign, .)
}
spikeAlign$Histone = factor(spikeAlign$Histone, levels = histList)
spikeAlign %>% mutate(AlignmentRate_spikeIn = paste0(AlignmentRate_spikeIn, "%"))

比對總結

##=== R command ===## 
alignSummary = left_join(alignResult, spikeAlign, by = c("Histone", "Replicate", "SequencingDepth")) %>%
  mutate(AlignmentRate_hg38 = paste0(AlignmentRate_hg38, "%"), 
         AlignmentRate_spikeIn = paste0(AlignmentRate_spikeIn, "%"))
alignSummary

可視化測序深度和比對結果

##=== R command ===## 
## Generate sequencing depth boxplot
fig3A = alignResult %>% ggplot(aes(x = Histone, y = SequencingDepth/1000000, fill = Histone)) +
    geom_boxplot() +
    geom_jitter(aes(color = Replicate), position = position_jitter(0.15)) +
    scale_fill_viridis(discrete = TRUE, begin = 0.1, end = 0.9, option = "magma", alpha = 0.8) +
    scale_color_viridis(discrete = TRUE, begin = 0.1, end = 0.9) +
    theme_bw(base_size = 18) +
    ylab("Sequencing Depth per Million") +
    xlab("") + 
    ggtitle("A. Sequencing Depth")

fig3B = alignResult %>% ggplot(aes(x = Histone, y = MappedFragNum_hg38/1000000, fill = Histone)) +
    geom_boxplot() +
    geom_jitter(aes(color = Replicate), position = position_jitter(0.15)) +
    scale_fill_viridis(discrete = TRUE, begin = 0.1, end = 0.9, option = "magma", alpha = 0.8) +
    scale_color_viridis(discrete = TRUE, begin = 0.1, end = 0.9) +
    theme_bw(base_size = 18) +
    ylab("Mapped Fragments per Million") +
    xlab("") +
    ggtitle("B. Alignable Fragment (hg38)")

fig3C = alignResult %>% ggplot(aes(x = Histone, y = AlignmentRate_hg38, fill = Histone)) +
    geom_boxplot() +
    geom_jitter(aes(color = Replicate), position = position_jitter(0.15)) +
    scale_fill_viridis(discrete = TRUE, begin = 0.1, end = 0.9, option = "magma", alpha = 0.8) +
    scale_color_viridis(discrete = TRUE, begin = 0.1, end = 0.9) +
    theme_bw(base_size = 18) +
    ylab("% of Mapped Fragments") +
    xlab("") +
    ggtitle("C. Alignment Rate (hg38)")

fig3D = spikeAlign %>% ggplot(aes(x = Histone, y = AlignmentRate_spikeIn, fill = Histone)) +
    geom_boxplot() +
    geom_jitter(aes(color = Replicate), position = position_jitter(0.15)) +
    scale_fill_viridis(discrete = TRUE, begin = 0.1, end = 0.9, option = "magma", alpha = 0.8) +
    scale_color_viridis(discrete = TRUE, begin = 0.1, end = 0.9) +
    theme_bw(base_size = 18) +
    ylab("Spike-in Alignment Rate") +
    xlab("") +
    ggtitle("D. Alignment Rate (E.coli)")

ggarrange(fig3A, fig3B, fig3C, fig3D, ncol = 2, nrow=2, common.legend = TRUE, legend="bottom")

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