This question was closed but I am asking a different way to discover lost/acquired super enhancers in normal vs. breast cancer cells. Please let do not close this question. So briefly, I did ChIP seq using H3K27ac antibody to quantify super enhancer regions in normal vs breast cancer cells. I ran ROSE algorithm on normal mammary epithelial cells and breast cancer cells to get a list of super enhancer regions in each cell line. I have a list of super enhancer regions for both and I want to compare super enhancers between the two outputs I got. I want to compare the signal of the super enhancer regions that were classified by ROSE in normal and breast cancer cells and see calculate fold change of those regions to see if they are increasing or decreasing in intensity. I have a bed files of super enhancer regions for normal cells (MCF10A) and same for breast cancer cells (MCF10A-CA1). I know what I have to do. Briefly, collapse A.SE.bed and B.SE.bed into AllSEs.bed using bedtools merge. Quantify coverage of All SEs.bed using A.bam and B.bam and bedtools intersect. Normalize the read coverage to the sequencing depth, and calculate the fold-change between them. The problem I was having is how can I collapse or merge two or three bed files into one file that will contain all the super enhancer regions classified and quantify coverage? Any help is appreciated. Thank you so much!
