Hi,

I'm attempting to smooth genome-wide data that is currently in a bedGraph format in an attempt to remove problems visualising the data which is skewed toward single 1bp peaks with high signal amongst regions of low signal - such as the one highlighted below:

chrI 86 87 1

chrI 108 109 1

chrI 297 298 1

chrI 395 396 1

chrI 399 400 1

chrI 411 412 455

chrI 413 414 1

chrI 414 415 1

chrI 416 417 2

Within MatLab i've carried out smoothing by using a Hann window, creating it with:

hann15=hanning(15);

and smoothing the signal with:

smooth15=conv(signal,hann15,'same');

However i've noticed that if I manually alter signal data to include an aberrantly strong peak of the kind we are trying to reduce the prevalence of - this smoothing method includes the new value and constructs a smoothed peak bias toward this one outlier.

Is there a way to get around this? Perhaps I need a new smoothing window shape?

Thanks for any help!

• TJC