You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I'm running bdgcallpeak on a bedGraph file optained from an input normalised bigwig file (operation used was subtraction). The minimum value in the file is approximately -5000, and the maximum is approx 1600. Therefore, when running bdgcallpeak with cutoff-analysis to see how many peaks different thresholds yield, I get this output:
A lot of these results are useless, as they explore negative cutoffs that end up lumping large amounts of the genomes together into "peaks". More control over the cutoffs tested by cutoff-analysis could give me better insight into the distribution of my data.
One basic solution would be to add a "no-negative" option, which prevents cutoff-analysis from considering negative thresholds, which seems relevant when dealing with data normalised like mine. A more in-depth approach would be to let the user specify the min, max and step to use to calculate the cutoffs (which I assume is what cutoff-analysis with cutoff-analysis-steps does, but using the min and max in the file) to allow full control, but I don't know how feasible that is.
Currently I'm rerunning the analysis with 500 cutoffs, but still more than half of them will be unusable.
The text was updated successfully, but these errors were encountered:
@callum-b I have added the options to control the upper bound (max) and step of the cutoff analysis. You can find in the master branch. Clone the master branch git clone https://github.com/macs3-project/MACS/ and follow this instruction. To add a lower bound (min) is a good idea too. I will add it soon. Thanks!
I'm running bdgcallpeak on a bedGraph file optained from an input normalised bigwig file (operation used was subtraction). The minimum value in the file is approximately -5000, and the maximum is approx 1600. Therefore, when running bdgcallpeak with cutoff-analysis to see how many peaks different thresholds yield, I get this output:
A lot of these results are useless, as they explore negative cutoffs that end up lumping large amounts of the genomes together into "peaks". More control over the cutoffs tested by cutoff-analysis could give me better insight into the distribution of my data.
One basic solution would be to add a "no-negative" option, which prevents cutoff-analysis from considering negative thresholds, which seems relevant when dealing with data normalised like mine. A more in-depth approach would be to let the user specify the min, max and step to use to calculate the cutoffs (which I assume is what cutoff-analysis with cutoff-analysis-steps does, but using the min and max in the file) to allow full control, but I don't know how feasible that is.
Currently I'm rerunning the analysis with 500 cutoffs, but still more than half of them will be unusable.
The text was updated successfully, but these errors were encountered: