text: user7056: I recently received some .bigwig files from a chipseq experiment.
  I loaded the files into IGV.
  The interpretation is rather intuitive.
  My question is the following:
  What exactly do the track heights represent?
  For IgG control, the track height is low ranging from 0~5.
  For positive controls, such as H3K4me3, I see clear peaks with height ~100.
  Do track heights simply mean the number of reads mapped to that genomic interval during peak calling?
  Does it literally mean there are ~100 reads that aligned to that region in the H3K4me3 .bam file?
  Thanks so much.
  
  user-1: Depends how the files were made. In the simplest case yes, the height represents the pipeup of reads from the BAM file that was used. For a direct (visual) comparison you have to normalize the files though as otherwise sequencing depth confounds the height of the peaks, like if file A has ten times more reads and the peak is 10 times higher than in B then this is probably only due to differences in total read number (=sequencing depth). I wrote down my preferred method to do that in this biostars post: https://www.biostars.org/p/413626/#414440
  Does this make sense to you?
  
original_text: 7056: <p>I recently received some .bigwig files from a chipseq experiment.
  I loaded the files into IGV.</p>
  <p>The interpretation is rather intuitive.</p>
  <p>My question is the following:
  What exactly do the track heights represent?</p>
  <p>For IgG control, the track height is low ranging from 0~5.</p>
  <p>For positive controls, such as H3K4me3, I see clear peaks with height ~100.</p>
  <p>Do track heights simply mean the number of reads mapped to that genomic interval during peak calling?
  Does it literally mean there are ~100 reads that aligned to that region in the H3K4me3 .bam file?</p>
  <p>Thanks so much.</p>
   -1: <p>Depends how the files were made. In the simplest case yes, the height represents the pipeup of reads from the BAM file that was used. For a direct (visual) comparison you have to normalize the files though as otherwise sequencing depth confounds the height of the peaks, like if file A has ten times more reads and the peak is 10 times higher than in B then this is probably only due to differences in total read number (=sequencing depth). I wrote down my preferred method to do that in this biostars post: <a href="https://www.biostars.org/p/413626/#414440" rel="nofollow noreferrer">https://www.biostars.org/p/413626/#414440</a></p>
  <p>Does this make sense to you?</p>
  