MA.pcc: Deduce Pearson Correlation Coefficient between M & A Values
In yancychy/DiffChIPL: ChIP-seq differential analysis (DiffChIPL)
MA.pcc R Documentation
Deduce Pearson Correlation Coefficient between M & A Values
Description
Deduce Pearson Correlation Coefficient between M & A Values
Usage
MA.pcc(x, y)
Arguments
x, y
Two numeric vectors representing the signal intensities of two
samples.
Value
Safely deduced PCC between (x + y) and (y - x).
Examples
MA.pcc(1:4, 1:4 + c(1, 2, 4, 9))
# The robustness.
MA.pcc(1, 0)
MA.pcc(1:4, 2:5)
yancychy/DiffChIPL documentation built on Dec. 24, 2024, 11:26 p.m.
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| MA.pcc | R Documentation |
Deduce Pearson Correlation Coefficient between M & A Values
Description
Deduce Pearson Correlation Coefficient between M & A Values
Usage
MA.pcc(x, y)
Arguments
x, y |
Two numeric vectors representing the signal intensities of two samples. |
Value
Safely deduced PCC between (x + y) and (y - x).
Examples
MA.pcc(1:4, 1:4 + c(1, 2, 4, 9))
# The robustness.
MA.pcc(1, 0)
MA.pcc(1:4, 2:5)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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