fjcamlab/deco: Decomposing Heterogeneous Cohorts using Omic Data Profiling
This package discovers differential features in hetero- and homogeneous omic data by a two-step method including subsampling LIMMA and NSCA. DECO reveals feature associations to hidden subclasses not exclusively related to higher deregulation levels.
Getting started
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Package details |
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| Author | Francisco Jose Campos-Laborie, Jose Manuel Sanchez-Santos and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain. |
| Bioconductor views | Bayesian BiomedicalInformatics Clustering DifferentialExpression ExonArray FeatureExtraction GeneExpression MicroRNAArray Microarray MultipleComparison Proteomics RNASeq Sequencing Software Transcription Transcriptomics mRNAMicroarray |
| Maintainer | Francisco Jose Campos Laborie <fjcamlab@gmail.com> |
| License | GPL (>=3) |
| Version | 1.9.3 |
| URL | https://github.com/fjcamlab/deco |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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