ADAM - ADAM: Activity and Diversity Analysis Module
ADAM is a GSEA R package created to group a set of genes from comparative samples (control versus experiment) belonging to different species according to their respective functions (Gene Ontology and KEGG pathways as default) and show their significance by calculating p-values referring togene diversity and activity. Each group of genes is called GFAG (Group of Functionally Associated Genes).
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genesetenrichmentpathwayskegggeneexpressionmicroarraycpp
4.89 score 1 dependents 13 scripts 465 downloadslevi - Landscape Expression Visualization and Network Inference
Projects gene expression onto the plane of a biological network and draws it as a landscape: a Gaussian-kernel weighted surface on an absolute scale where 0.5 means no change. Regions of the landscape are tested by permutation, either conditional on the network and layout (node-label shuffling, maximum regional mass) or against biological replication (sample-label permutation, with blocking). Graph-native tests complement the landscape: threshold-free cluster enhancement on network components, Moran and Getis-Ord autocorrelation, Laplacian smoothness, Freedman-Lane residual permutation with covariates and degree-preserving rewiring nulls. Pseudobulk workflows for single-cell RNA-seq permute donors rather than cells. Adapters read DESeq2, edgeR, limma and Seurat results, SummarizedExperiment objects and STRING networks. A Shiny interface covers the interactive visualization.
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geneexpressionmicroarraysequencingrnaseqnetworkgraphandnetworkstatisticalmethodsoftwarevisualizationguigenesetenrichmentdifferentialexpressionsinglecellproteomicscpp
4.08 score 1 stars 6 scripts 378 downloadsADAMgui - Activity and Diversity Analysis Module Graphical User Interface
ADAMgui is a Graphical User Interface for the ADAM package. The ADAMgui package provides 2 shiny-based applications that allows the user to study the output of the ADAM package files through different plots. It's possible, for example, to choose a specific GFAG and observe the gene expression behavior with the plots created with the GFAGtargetUi function. Features such as differential expression and foldchange can be easily seen with aid of the plots made with GFAGpathUi function.
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genesetenrichmentpathwayskegg
3.30 score 1 scripts 421 downloads