Find super enhancers like you normally would, but add the option "-superSlope -1000" - the idea is to include ALL potential peaks as 'super enhancers' so that we can plot them together. Open the resulting peak file in Excel. The 6th column ("Normalized Tag Count") contains the super enhancer score for each region. Simply ploting this column as a line plot will give you a sense of what your plot will look like. To get an official "Young-lab style" plot you'll have to do some Excel algebra to normalize score by the total.
嗯,含糊其辞。不知道这个normalization方法到底是什么。
然后看看ROSE的CalllSuper.R
对我来说有点难度。。。。
所以问题来了,请问有人能根据homer生成的superEnhancers.txt画出ROSE的那种图嘛
附上表格header及前两行数据,以及SE图的示例。
#]#]# Peak finding parameters:
#]#]#
#]#]# super enhancer stitching window = 12500
#]#]# super enhancer slope moving window = 10
#
<span]#
<span]# total peaks = 34910
#]#]# peaks found using tags on both strands
#]#]# fragment length = 262
#]#]# Total tags = 19369571.0
#]#]# Approximate IP efficiency = 55.94%
#]#]# expected tags per peak = 2.847
#]#]# effective number of tags used for normalization = 10000000.0
#]#]# FDR rate threshold = 0.001000000
#]#]# FDR tag threshold = 14.0
#]#]#
#]#]# Fold over local region required = 4.00
#]#]# Putative peaks filtered by local signal = 485963
#
<span]#
<span]# Maximum fold under expected unique positions for tags = 2.00
#]#]#
#]#]#
#]#]#PeakID chr start end strand Normalized Tag Count superEnhancer slope findPeaks Score Fold Change vs Local p-value vs Local Clonal Fold Change
chr3-27789<span]chr3-27789<span]chr6-2384 chr6 30710774 30769390 + 4826.6 58616.000 151.000000 4.47 5.64e-51 0.78
chr19-5188<span]chr19-5188<span]chr5-9537 chr5 111272574 111360908 + 4083.7 88334.000 75.000000 4.30 7.80e-24 0.89
chr1-45761 chr1 235091137 235134056 + 3987.7 42919.000 28.000000 7.21 8.45e-18 0.95