You could try taking an average the signal of a window i.e. 0 to 500 bp after the TSS for both the red and blue lines (peaks). Then You could take an average of the signal where these proteins are not enriched i.e. -2500 to -2000 bp before the transcription start site for both the blue and red lines (trough). You will now have four numbers, red line peak and trough and blue line peak and trough averages. Now perform a Chi-square test where the expected range is the blue line and the actual is the red line numbers. This will give you a p-value.

in excel it would look like this:
=CHITEST(red peak avg.:red trough avg., blue peak avg.:blue trough avg.

or (using estimates just by looking at the graph)

=CHITEST(0.28:0.055,0.11:0.033)

Another way could be just to use the raw signal values and do a chi-square test on the red and blue lines so something like this: =CHITEST(red signal -2500:red signal 2500, blue signal -2500:blue signal 2500)
-In this method you would be using all the data points, not just averages.

**Other ways/caveats:**

-Instead of using just the red and blue line averages, include the Ig (mock IP) control by using ratios i.e. (blue line average peak)/ (black line average peak). This will still give you four numbers at the end, but they will all be ratios.

-You may want to consult a stats person too, because I'm not sure if a chi-square test is the best for answering your question, but it will give you a p-value.

-I'm not sure what p-value would be considered significant.

I'm interested in hearing what others have to say about this because I too have wondered if there was a proper way to do such an analysis.

use this tool

https://github.com/shenlab-sinai/ngsplot