| ALICOR {encoDnaseI} | R Documentation |
aligned and interpolated correlation for local maximum traces from two scatterplots
alicor(x1, y1, x2, y2, bin = 50000) ALICOR(ssr, dns = rawCD4, bin = 50000)
x1 |
domain points for first scatterplot |
y1 |
range points for first scatterplot |
x2 |
domain points for second scatterplot |
y2 |
range points for second scatterplot |
ssr |
an instance of class snpScreenResult |
dns |
an instance of class hg18track |
bin |
bin size, units are base pairs |
We define a scatterplot to be a pair of vectors (x, y). We are interested in measuring the distance between two scatterplots, focusing on the locations of local peaks and valleys. Two scatterplots are close if their peaks and valleys in y are nearby in x.
We have no restrictions on commonalities between the scatterplots, but this only makes sense if there is reasonable overlap between their x ranges.
The algorithm, implemented in low-level function
alicor, is as follows. Use parameter bin to
define a grid in x for each scatterplot, and compute the maximum
y value in each x-grid interval. Compute a common domain
for the two scatterplots based solely on x1.
Linearly interpolate the maximal series for
each scatterplot on the common domain. Compute the correlation coefficient
for the resulting interpolated series.
The higher-level function ALICOR adapts this to snpScreenResult
plot_mlp display data and to hg18 annotation track data.
scalar correlation coefficient
Many variations on this algorithm are possible, but the code is not very flexible at this time.
VJ Carey <stvjc@channing.harvard.edu>
data(sOSR2) data(c19g) juxtaPlot(c19g, sOSR2) ALICOR(sOSR2, c19g)