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(c) Contour plot of cross-correlation coefficient.
Figure 2 Shown is the plot of cross-correlation function between two non-overlapping segments (35 msec.
Shown in Figure 2 is the plot of cross-correlation function of two non-overlapping segments (35 msec. apart) of a decaying tail of same "hand-clap" recorded using microphone M i c 1 in a restroom (a highly reverberant environment, E5).
And, shown in Figure 3 is the plot of cross-correlation function of two time-aligned segments of decaying tails of identical "hand-clap" recordings made at two different time instances with M i c 1 in E5 (i.e., by playing the same "hand-clap" recording twice).
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In general, we recommend manual examination of cross-correlation plots in all cases.
We provide representative examples of cross-correlation plots for each of the five QC categories in Figure S1A, and we use these tags as convenient general proxies for ChIP quality throughout the following analysis.
Figure S1B shows examples of cross-correlation plots for individual control datasets with all possible QC scores, from −2 to 2, and Figure 3C shows a browser snapshot of a region with strong read enrichment in a highly clustered (QC score of 2) input library.
The algorithm first uses a TF plot to manually pick a reference first-break and then iterates the steps of cross-correlation, alignment, and stacking to enhance the signal-to-noise ratio of the relative first breaks.
b Distribution of cross-correlation.
The level of cross-correlation.
Fig. 5 Ramp function and examples of cross-correlation.
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