A pipeline for the meta-analysis of gene expression data. We have assembled several analysis and plot functions to perform integrated multi-cohort analysis of gene expression data (meta-analysis).
COmbat CO-Normalization Using conTrols (COCONUT)
Allows for pooled analysis of microarray data by batch-correcting control samples, and then applying the derived correction parameters to non-control samples to obtain bias-free, inter-dataset corrected data.
Our data represent meta-analysis of gene expression microarrays across diseases to identify consistent gene expression signatures in a specific disease state.
immunoStates allows estimating percentages of various immune cells using transcriptome data in a whole blood or PBMC sample. It is a basis matrix composed of 317 genes that represent 20 immune cell types. immunoStates is now integrated in MetaIntegrator. (More information)
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