deeptools辅助CHIP-seq数据分析-可视化

ulwvfje — Thu, 15 Dec 2016 11:20:00 +0000

有很多读者来信，CHIP-seq数据比对后的bam文件如果根据基因组的所有基因来画热图，profile图呢？

这里隆重推荐deeptools这个软件：

第一个功能，把bam文件转换为bw格式文件：

bamCoverage -b tmp.sorted.bam -o tmp.bw

里面有一个参数非常重要，就是--extendReads 在 macs软件里面也有，macs2 pileup --extsize 200 ，就算是你的reads长度可能不一致，是否需要把它们补齐成一个统一的长度，因为我们只要是测到了reads，就代表那里是有signal的，只是因为我们的测序仪限制，测到的长度不够，或者质量不好，我们QC的时候，把前后碱基给trim掉了。还可以安装基因组的有效大小来对测序深度进行normlization。

第二个功能，画所有基因附近的信号热图，tools: computeMatrix, then plotHeatmap

http://deeptools.readthedocs.io/en/latest/content/example_step_by_step.html#heatmaps-and-summary-plots

需要自行下载合适的基因坐标记录文件，BED格式的。把上面两个命令结合起来即可，代码和图形实例如下:

第3个功能，画profile的图！

use computeMatrix for all of the signal files (bigWig format) at once

use plotProfile on the resulting file

还有很多小功能，欢迎大家去探索，这个软件是python软件，安装非常简单：

## Download and install deepTools

## https://github.com/fidelram/deepTools

## http://deeptools.readthedocs.io/en/latest/content/example_usage.html

pip install pyBigWig --user

cd ~/biosoft

mkdir deepTools && cd deepTools

git clone https://github.com/fidelram/deepTools ## 130M,

cd deepTools

python setup.py install --user

## 17 tools in ~/.local/bin/

~/.local/bin/deeptools

安装之后，很多小工具都放到了~/.local/bin/目录：

如果你有大批量的bam文件，需要批量做，用下面的脚本啦：

ls ../bamFiles/*bam |while read id

do

file=$(basename $id )

sample=${file%%.*}

echo $sample

bamCoverage -b $id -o $sample.bw

computeMatrix reference-point --referencePoint TSS -b 10000 -a 10000 -R ~/annotation/CHIPseq/mm10/ucsc.refseq.bed -S $sample.bw --skipZeros -o matrix1_${sample}_TSS.gz --outFileSortedRegions regions1_${sample}_genes.bed

plotHeatmap -m matrix1_${sample}_TSS.gz -out ${sample}.png

done

热图最佳实践-pheatmap

ulwvfje — Thu, 03 Nov 2016 02:30:21 +0000

用pheatmap来绘图首先要安装这个包，它就一个功能，画出热图即可，号称是pretty heatmap，的确比其它的好用很多。我以前写过《一步一步学习heatmap.2》的教程，很简单的那种，所以就没有公布在博客上面，结果发现很多其它博客居然能先我一步发出。其实包括本次的pheatmap指南，都没什么好发，的在R里面也是傻瓜式出图，无法就是自己熟练一下参数而已，又不是开发一个包，没什么技术含量。我这里单独提一下pheatmap是因为它的确非常好用，将会是我画热图的不二之选。比如下面这个，是我最喜欢的：

里面该有的信息一应俱全了，包括基因可以分成上下调来显色，基因和样本都可以单独聚类，单独排序，样本也可以具体再分组。热图也可以调整配色方案，单元格的宽度和高度都可以自由调整。把它说明书的代码一句句运行一遍就明白了：ftp://cran.r-project.org/pub/R/web/packages/pheatmap/pheatmap.pdf

代码如下：

## PS：我代码复制到博客就中英文标点被弄混了，请不要直接复制我的点，一行行点敲到R里面

## ftp://cran.r-project.org/pub/R/web/packages/pheatmap/pheatmap.pdf
# Create test matrix
## Just replace the test matrix with your own data.
test = matrix(rnorm(200), 20, 10)
test[1:10, seq(1, 10, 2)] = test[1:10, seq(1, 10, 2)] + 3
test[11:20, seq(2, 10, 2)] = test[11:20, seq(2, 10, 2)] + 2
test[15:20, seq(2, 10, 2)] = test[15:20, seq(2, 10, 2)] + 4
colnames(test) = paste("Test", 1:10, sep = "")
rownames(test) = paste("Gene", 1:20, sep = "")
# Draw heatmaps
pheatmap(test)
pheatmap(test, kmeans_k = 2)
pheatmap(test, scale = "row", clustering_distance_rows = "correlation")
pheatmap(test, color = colorRampPalette(c("navy", "white", "firebrick3"))(50) )
pheatmap(test, cluster_row = FALSE)
pheatmap(test, legend = FALSE)
# Show text within cells
pheatmap(test, display_numbers = TRUE)
pheatmap(test, display_numbers = TRUE, number_format = "\%.1e")
pheatmap(test, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test)))
pheatmap(test, cluster_row = FALSE, legend_breaks = -1:4, legend_labels = c("0",
"1e-4", "1e-3", "1e-2", "1e-1", "1"))
# Fix cell sizes and save to file with correct size
pheatmap(test, cellwidth = 15, cellheight = 12, main = "Example heatmap")
pheatmap(test, cellwidth = 15, cellheight = 12, fontsize = 8, filename = "test.pdf")
# Generate annotations for rows and columns
annotation_col = data.frame(
CellType = factor(rep(c("CT1", "CT2"), 5)),
Time = 1:5
)
rownames(annotation_col) = paste("Test", 1:10, sep = "")
annotation_row = data.frame(
GeneClass = factor(rep(c("Path1", "Path2", "Path3"), c(10, 4, 6)))
)
rownames(annotation_row) = paste("Gene", 1:20, sep = "")
# Display row and color annotations
pheatmap(test, annotation_col = annotation_col)
pheatmap(test, annotation_col = annotation_col, annotation_legend = FALSE)
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row)
# Specify colors
ann_colors = list(
Time = c("white", "firebrick"),
CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E")
)
pheatmap(test, annotation_col = annotation_col, annotation_colors = ann_colors, main = "Title")
pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row,
annotation_colors = ann_colors)
pheatmap(test, annotation_col = annotation_col, annotation_colors = ann_colors[2])
# Gaps in heatmaps
pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14))
pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14),
cutree_col = 2)
# Show custom strings as row/col names
labels_row = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "",
"", "", "Il10", "Il15", "Il1b")
pheatmap(test, annotation_col = annotation_col, labels_row = labels_row)
# Specifying clustering from distance matrix
drows = dist(test, method = "minkowski")
dcols = dist(t(test), method = "minkowski")
pheatmap(test, clustering_distance_rows = drows, clustering_distance_cols = dcols)
# Modify ordering of the clusters using clustering callback option
callback = function(hc, mat){
sv = svd(t(mat))$v[,1]
dend = reorder(as.dendrogram(hc), wts = sv)
as.hclust(dend)
}
pheatmap(test, clustering_callback = callback)
## Not run:
# Same using dendsort package
library(dendsort)
callback = function(hc, ...){dendsort(hc)}
pheatmap(test, clustering_callback = callback)
## End(Not run)

生信菜鸟团 » 热图

deeptools辅助CHIP-seq数据分析-可视化

热图最佳实践-pheatmap