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
