I would like to know about different meta-analysis packages of gene expression data.

1) As i know, MetaQC is used to check the quality of gene expression studies. I would like to know how to interpret the result of MetaQC. I used the benchmark brain data to perform MetaQC. 

brainQC <- MetaQC(brain, "c2.cp.biocarta.v5.0.symbols.gmt",
                  filterGenes=FALSE, verbose=TRUE)
runQC(brainQC, B=1e2, fileForCQCp="c2.all.v5.0.symbols.gmt")
brainQC

I got the results :

Number of Studies:  7

Dimension of Each Study:
        Petalidis Freije Phillips  Sun Paugh Yamanaka Gravendeel
Genes         793   1119     1119 1232  1232      424       1083
Samples        58     85      100  100    42       29        175

Quality Control Result:
       Study   IQC   EQC   CQCg   CQCp  AQCg  AQCp Rank
1  Petalidis  4.38 0.83* 307.65 133.86 32.71 82.01 2.75
2        Sun  4.96 1.53* 307.65 101.51 30.42 29.94 2.75
3 Gravendeel  5.27    2*   19.1  90.31  8.24 58.61 3.00
4     Freije  5.75  1.7* 307.65  35.54 19.03 10.66 3.25
5   Phillips  5.11 0.64* 307.65  60.02 29.49 29.18 3.92
6      Paugh 1.21* 1.23*  1.16*  1.69* 0.31*  3.56 6.00
7   Yamanaka 0.23* 1.31*  0.09*  1.89* 0.05* 0.36* 6.33

What it tells me regarding the inclusion/exclusion of particular study. What is the criteria to include/exclude??

2). Can we exclude a study which does not meet the standards on the fly and pass the other studies to MetaDE or MetaPath for further analysis.

3). Or we need to use each of the three packages independently. Is there  a concept of pipeline with all the three packages in the sense that the output of MetaQC goes as input to MetaDE and output of MetaDE goes as input to MetaPath.