Hello,
For H3K36ME3, I got four sequencing reads samples. After alignment, I got four bam files. Afterwards, I combine those four bam files into one big bam file. Finally I got one bigwig files from the big bam file using bamcoverage command.
For H3K79me2, I got two sequencing reads samples. After alignment, I got two bam files. Afterwards, I combine those two bam files into one big bam file. Finally I got one bigwig files from the big bam file using bamcoverage command.
Now, I would like to explore H3K36ME3 and H3K79me2 signal around TSS using deeptools according the above two bigwig files. I wonder whether or not I could compare H3K36Me3 and H3K79me2 signal? (Because H3K36ME3 signal is from four bam files, H#K79ME2 is from two bam files. Do I need to double H3K79ME2 first and then compare H3K36Me3 and H3K79me2 signal?)
Thank you in advance.
The question you asked is about ChIP-seq normalization, it has nothing to do with how many bam files you have. What you should care about is the sequencing depth and the distribution of reads across the genome, there have been many methods proposed to solve this problem, like quantile normalization, SES, NCIS and so on.
For your samples, since histone modification is not like transcription factor, it has broader binding sites and weaker peaks. Most normalization methods designed for TF are not suitable for you, you can start by normalizing sequence depth and some methods specially designed for histone modifications.