JumpTest (version 1.1)

ppool: p-values pooling and adjustment

Description

Pooling input p-values and perfrom FDR adjustments

Usage

ppool(pmat, method = "SD")

Arguments

pmat

p-values matrix stored by columns

method

pooling methods, see details

Value

stat

pooled test statistcs

pvalue

pooled p-values

adjp

pooled p-values via "BH" adjustments

Details

for p-values poolings, we provided six methods. "FI" for Fisher's method, "FD" for Fisher's with correlation adjustments, "SI" for Stouffer's method, "SD" for Stouffer's method with correlation adjustments, "MI" for minimum p-value methods, and "MA" for maximum p-value method

References

Benjamini, Y. and Y. Hochberg (1995). "Controlling the false discovery rate: a practical and powerful approach to multiple testing." Journal of the Royal Statistical Society. Series B (Methodological): 289-300.

Chang, L.-C., et al. (2013). "Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline." BMC bioinformatics 14(1): 368.

Won, S., et al. (2009). "Choosing an optimal method to combine P-values." Statistics in medicine 28(11): 1537-1553.

Alves, G., & Yu, Y. K. (2014). Accuracy evaluation of the unified P-value from combining correlated P-values. PloS one, 9(3), e91225.

Examples

# NOT RUN {
orip <- matrix(runif(3000),1000,3)
pvobj <- ppool(orip)
pvalue <- pvobj@pvalue
padjust <- pvobj@adjp
# }