EmpiricalBayesPrior: Computes the prior parameters (i.e. pseudocounts incremented...
In erhard-lab/lfc: Log Fold Change Distribution Tools for Working with Ratios of Counts
EmpiricalBayesPrior R Documentation
Computes the prior parameters (i.e. pseudocounts incremented by 1) for
the log2 fold change distribution
Description
Computes the prior parameters (i.e. pseudocounts incremented by 1) for
the log2 fold change distribution
Usage
EmpiricalBayesPrior(A, B, min.sd = 0)
Arguments
A
Vector of counts from condition A
B
Vector of counts from condition B
min.sd
minimal standard deviation of the prior
Value
A vector of length 2 containing the two parameters
See Also
PsiLFC
Examples
EmpiricalBayesPrior(rnorm(1000,200),rnorm(1000,100))
erhard-lab/lfc documentation built on April 25, 2023, 6:59 a.m.
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| EmpiricalBayesPrior | R Documentation |
Computes the prior parameters (i.e. pseudocounts incremented by 1) for the log2 fold change distribution
Description
Computes the prior parameters (i.e. pseudocounts incremented by 1) for the log2 fold change distribution
Usage
EmpiricalBayesPrior(A, B, min.sd = 0)
Arguments
A |
Vector of counts from condition A |
B |
Vector of counts from condition B |
min.sd |
minimal standard deviation of the prior |
Value
A vector of length 2 containing the two parameters
See Also
PsiLFC
Examples
EmpiricalBayesPrior(rnorm(1000,200),rnorm(1000,100))
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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