conumee
conumee performs copy-number variation (CNV) analysis and visualization from Illumina 450k and EPIC methylation array data.
Key Features:
- Array support: Processes signal data derived specifically from Illumina 450k and EPIC methylation arrays for CNV analysis.
- R implementation: Implemented in the R programming language and uses Bioconductor data structures and functions.
- Processing and plotting: Provides processing and plotting methods tailored for CNV detection and visualization from methylation array data.
- Quality control and testing: Distributed within Bioconductor and subject to Bioconductor initial review and continuous automated testing.
Scientific Applications:
- Cancer research: Identification and visualization of somatic and germline CNVs relevant to oncogenesis and tumor progression.
- Genetic disorder analysis: Detection of CNVs linked to hereditary conditions and structural genomic variation.
- Epigenetics studies: Investigation of relationships between DNA methylation patterns and copy-number changes.
Methodology:
Implements statistical processing and visualization methods in R/Bioconductor to analyze CNV signals derived from Illumina 450k and EPIC methylation arrays.
Topics
Collections
Details
- License:
- GPL-2.0
- Tool Type:
- command-line tool, library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 1/17/2017
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
Copy number estimation
Publications
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M. Orchestrating high-throughput genomic analysis with Bioconductor. Nature Methods. 2015;12(2):115-121. doi:10.1038/nmeth.3252. PMID:25633503. PMCID:PMC4509590.