Description Usage Arguments Value Author(s)
Predict EDR based on a pilot data.
1 2 3 | Estimate.EDR.from.pilot(Data, status, group.name = c("Control", "Case"), FDR,
M, target.N, target.R = NULL, target.theta = NULL, tol = 0.1,
filter = T, filter.level = 5)
|
Data |
Input pilot data. |
status |
A vector of group labels. |
group.name |
A vector of length two. First element is the group name of first group, and the second element is of second group. |
FDR |
FDR level. |
M |
Number of iterations for parametric bootstrap. |
target.N |
Targeted sample size. |
target.R |
Targeted sequencing depth. |
target.theta |
Targeted proportion of sample size in second group compared to first group. |
tol |
Threshold for deciding if use CDD to estimate the proportion of DE genes. |
filter |
Filter genes based on mean counts? |
filter.level |
Filter the genes with mean counts less than this level. |
An object of class list is returned: Result is a list of length M (depends on how many times of parametric bootstrap you run), and each component is also a list of length of variable target.R. Each component contains a matrix with target N in row and summary statistics in columns. Summary statistics provided are TP, TN, EDR.
Chien-Wei Lin
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