# MetaDE.pvalue

From MetaDE v1.0.5
by Xingbin Wang

##### Identify differentially expressed genes by combining p-values

`MetaDE.pvalue`

Identify differentially expressed genes by integrating multiple studies(datasets). The data
consists of p-values from your own method/calculations.

- Keywords
- Meta-analysis DE genes

##### Usage

```
MetaDE.pvalue(x, meta.method = c("maxP", "maxP.OC", "minP",
"minP.OC", "Fisher", "Fisher.OC", "AW", "AW.OC",
"roP", "roP.OC", "Stouffer", "Stouffer.OC", "SR",
"PR"), rth = NULL, miss.tol = 0.3, asymptotic = FALSE)
```

##### Arguments

- x
- a list with components:
**p**: a list of p values for each dataset.**bp**: a list of p values calculated from permutation for each dataset. This part can be NULL if you just have the p-values from your own method.

- meta.method
- a character to specify the type of Meta-analysis methods to combine the p-values or effect sizes. See "Detials".
- rth
- this is the option for roP and roP.OC method. rth means the rth smallest p-value.
- miss.tol
- The maximum percent missing data allowed in any gene (default 30 percent).
- asymptotic
- A logical values to specify whether the parametric methods is chosen to calculate the p-values in meta-analysis. The default is FALSE.

##### Details

The options for argument,`mete.method`

,are listed below:

**"maxP"**: the maximum of p value method.**"maxP.OC"**: the maximum of p values with one-sided correction.**"minP"**: the minimum of p values from "test" across studies.**"minP.OC"**: the minimum of p values with one-sided correction.**"Fisher"**: Fisher's method (Fisher, 1932),the summation of -log(p-value) across studies.**"Fisher.OC"**: Fisher's method with one-sided correction (Fisher, 1932),the summation of -log(p-value) across studies.**"AW"**: Adaptively-weighted method (Li and Tseng, 2011).**"AW.OC"**: Adaptively-weighted method with one-sided correction (Li and Tseng, 2011).**"roP"**: rth p-value method.**"roP.OC"**: rth p-value method with one-sided correction.**"Stouffer"**: the minimum of p values from "test" across studies.**"Stouffer.OC"**: the minimum of p values with one-sided correction.**"SR"**: the naive sum of the ranks method.**"PR"**: the naive product of the ranks method.

##### Value

- A list containing:
stat a matrix with rows reprenting genes. It is the statistic for the selected meta analysis method of combining p-values. pval the p-value from meta analysis for each gene for the above stat. FDR the FDR of the p-value for each gene for the above stat. AW.weight The optimal weight assigned to each dataset/study for each gene if the ' `AW`

' or '`AW.OC`

' method was chosen.

##### References

Jia Li and George C. Tseng. (2011) An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies. Annals of Applied Statistics. 5:994-1019. Shuya Lu, Jia Li, Chi Song, Kui Shen and George C Tseng. (2010) Biomarker Detection in the Integration of Multiple Multi-class Genomic Studies. Bioinformatics. 26:333-340. (PMID: 19965884; PMCID: PMC2815659)

##### See Also

MetaDE.minMCC, MetaDE.pvalue,MetaDE.ES,plot.FDR,heatmap.sig.genes

##### Examples

```
#---example 1: Meta analysis of Differentially expressed genes between two classes----------#
# here I generate two pseudo datasets
label1<-rep(0:1,each=5)
label2<-rep(0:1,each=5)
exp1<-cbind(matrix(rnorm(5*20),20,5),matrix(rnorm(5*20,2),20,5))
exp2<-cbind(matrix(rnorm(5*20),20,5),matrix(rnorm(5*20,1.5),20,5))
#the input has to be arranged in lists
x<-list(list(exp1,label1),list(exp2,label2))
# start individual analysis for each dataset: here I used modt to generate p-values.
DEgene<-ind.analysis(x,ind.method=c("modt","modt"),tail="high",nperm=100)
#you don't have to use our ind.analysis for the analysis for individual study. you can input
#p-values to MetaDE.pvalue for meta analysis only. But the input has to be specified in the
# same format as the DEgene in the example above
#--then you can use meta analysis method to combine the above p-values:here I used the Fisher's method
MetaDE.pvalue(DEgene,meta.method='Fisher')
```

*Documentation reproduced from package MetaDE, version 1.0.5, License: GPL-2*

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