View source: R/designSampleSizePTM.R
designSampleSizePTM | R Documentation |
Calculate sample size for future experiments of a PTM experiment based on intensity-based linear model. Calculation is only available for group comparison experimental designs (not including time series). Two options of the calculation: (1) number of biological replicates per condition, (2) power.
designSampleSizePTM(
data,
desiredFC,
FDR = 0.05,
numSample = TRUE,
power = 0.8,
use_log_file = TRUE,
append = FALSE,
verbose = TRUE,
log_file_path = NULL,
base = "MSstatsPTM_log_"
)
data |
output of the groupComparisonPTM function. |
desiredFC |
the range of a desired fold change which includes the lower and upper values of the desired fold change. |
FDR |
a pre-specified false discovery ratio (FDR) to control the overall false positive rate. Default is 0.05 |
numSample |
minimal number of biological replicates per condition. TRUE represents you require to calculate the sample size for this category, else you should input the exact number of biological replicates. |
power |
a pre-specified statistical power which defined as the probability of detecting a true fold change. TRUE represent you require to calculate the power for this category, else you should input the average of power you expect. Default is 0.9 |
use_log_file |
logical. If TRUE, information about data processing will be saved to a file. |
append |
logical. If TRUE, information about data processing will be added to an existing log file. |
verbose |
logical. If TRUE, information about data processing will be printed to the console. |
log_file_path |
character. Path to a file to which information about
data processing will be saved.
If not provided, such a file will be created automatically.
If |
base |
start of the file name. |
The function fits the model and uses variance components to calculate sample size. The underlying model fitting with intensity-based linear model with technical MS run replication. Estimated sample size is rounded to 0 decimal. The function can only obtain either one of the categories of the sample size calculation (numSample, numPep, numTran, power) at the same time.
data.frame - sample size calculation results including varibles: desiredFC, numSample, FDR, and power.
model.lf.msstatsptm = groupComparisonPTM(summary.data,
data.type = "LabelFree",
verbose = FALSE)
#(1) Minimal number of biological replicates per condition
designSampleSizePTM(data=model.lf.msstatsptm, numSample=TRUE,
desiredFC=c(2.0,2.75), FDR=0.05, power=0.8)
#(2) Power calculation
designSampleSizePTM(data=model.lf.msstatsptm, numSample=5,
desiredFC=c(2.0,2.75), FDR=0.05, power=TRUE)
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