biomvRCNS
In this package, a Hidden Semi Markov Model (HSMM) and one homogeneous segmentation model are designed and implemented for segmentation genomic data, with the aim of assisting in transcripts detection using high throughput technology like RNA-seq or tiling array, and copy number analysis using aCGH or sequencing.
- Bioconductor
- https://bioconductor.org/packages/biomvRCNS
Source attribution
- Bioconductor — biomvRCNS
Related resources
MEDIPS was developed for analyzing data derived from methylated DNA immunoprecipitation (MeDIP) experiments followed by sequencing (MeDIP-seq). However, MEDIPS provides functionalities for the analysis of any kind of quantitative sequencing data (e.g. ChIP-seq, MBD-seq, CMS-seq and others) including calculation of differential coverage between groups of samples and saturation and correlation analysis.
Pathview is a tool set for pathway based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.
This package is intended to identify differentially expressed genes driven by Copy Number Alterations from samples with both gene expression and CNA data.
Corrects GC and mappability biases for readcounts (i.e. coverage) in non-overlapping windows of fixed length for single whole genome samples, yielding a rough estimate of copy number for furthur analysis. Designed for rapid correction of high coverage whole genome tumour and normal samples.