EMMAWiki/WebDocumentation/AnalysisFunctions/SignificanceTest

Significance Test

Description

Test for significantly up- or down-regulated genes, by using either a t-test or wilcox-test. This method allows to compute adjusted p-values for the test. In addition, some more simple statistics are computed.

Input

Works for one or many normalized datasets.

Output

A table of data containing the following values:

• Statistic: The test statistik (either t or w value from the test)
• p-value: The p-value of the test statistik for this gene
• adjusted p-value: The adjusted p-value according to the adjustment method set
• M1-mean: The mean of the log-ratio over replicates
• ...

Parameters

• testtype Type of test to use [t.test | wilcox test]
• padj.method Chose method for adjusting the p.values [none | hommel | hochberg | fdr | bonferroni]
• two.sample Do a two-sample test? Otherwise one-sample test.

Details

SignificaneTest uses the R method p.adjust to compute adjusted p-values. Therefore, it provides the methods listed under padj.method. None will put the same as the unadjusted p-values.

References

Adjusted p-values (correct for multiple testing)

(the following references are taken from the R help page)

• Benjamini, Y., and Hochberg, Y. (1995). Controlling the false

    discovery rate: a practical and powerful approach to multiple
    testing. _Journal of the Royal Statistical Society Series_ B,

• 57*, 289-300.
• Holm, S. (1979). A simple sequentially rejective multiple test

    procedure. _Scandinavian Journal of Statistics_, *6*, 65-70.

• Hommel, G. (1988). A stagewise rejective multiple test procedure

    based on a modified Bonferroni test. _Biometrika_, *75*, 383-386

• Hochberg, Y. (1988). A sharper Bonferroni procedure for multiple

    tests of significance. _Biometrika_, *75*, 800-803.

• Shaffer, J. P. (1995). Multiple hypothesis testing. _Annual Review

    of Psychology_, *46*, 561-576. (An excellent review of the area.)

• Sarkar, S. (1998). Some probability inequalities for ordered MTP 2

    random variables: a proof of Simes conjecture. _Annals of
    Statistics_, *26*, 494-504.

• Sarkar, S., and Chang, C. K. (1997). Simes' method for multiple

    hypothesis testing with positively dependent test statistics.
    _Journal of the American Statistical Association_, *92*,
    1601-1608.

• Wright, S. P. (1992). Adjusted P-values for simultaneous

    inference. _Biometrics_, *48*, 1005-1013. (Explains the adjusted
    P-value approach.)