In broadinstitute/PerturbationAMARETTO: Regulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression
Run Information
Number of Samples in Gene Expression Data = r nExp
Number of Samples in DNA Copy Number Data = r nCNV
Number of Samples in DNA Methylation Data = r nMET
Number of r VarPercentage% most variable Genes = r nGenes
Number of Regulatory Modules = r nMod
Overview of Regulatory Modules
dt_overview
Assignments of Genes to Regulatory Modules
dt_genes
Enrichments of Functional Categories in Regulatory Modules
dt_genesetsall
<!--
Associations of Phenotypes to Regulatory Modules
phenotype_association_datatable
-->
broadinstitute/PerturbationAMARETTO documentation built on Nov. 4, 2019, 8:14 a.m.
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Run Information
Number of Samples in Gene Expression Data = r nExp
Number of Samples in DNA Copy Number Data = r nCNV
Number of Samples in DNA Methylation Data = r nMET
Number of r VarPercentage% most variable Genes = r nGenes
Number of Regulatory Modules = r nMod
Overview of Regulatory Modules
dt_overview
Assignments of Genes to Regulatory Modules
dt_genes
Enrichments of Functional Categories in Regulatory Modules
dt_genesetsall
<!--
Associations of Phenotypes to Regulatory Modules
phenotype_association_datatable
-->
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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