Hi, I would like to draw your attention towards two R packages released recently with Bioconductor 3.0. We would highly appreciate your feedbacks to help us improve them further. compEpiTools: Tools for computational epigenomics developed for the analysis, integration and simultaneous visualization of various (epi)genomics data types across multiple genomic regions in multiple samples. It broadly provide functionalities as: computing read counts of various data types in genomic regions, performing functional/genomic annotation, and integrated visualization of heterogeneous data-types. It facilitates several common operations associated to the quantification of the sequencing signal (ChIP-seq experiment) in a set of genomic regions. It provides fast, efficient batch annotation of genomic regions by UCSC database. It also provides functional annotation to characterize Enhancers and long non-coding RNAs. In addition some useful convenience function to perform GO enrichment analysis and classification of promoters based on CpG content. Method for integration of heterogeneous data based on heatmap visualization. methylPipe: Memory efficient analysis of base resolution DNA methylation data in both the CpG and non-CpG sequence context. Integration of DNA methylation data derived from any methodology providing base- or low-resolution. Simultaneous data visualization of methylation data heterogeneous in terms of resolutions together with other omics data and gene models. Identification of genome wide and region centric differentially methylated regions (DMRs) for pairwise and multi-sample comparisons. Important quality control measurement in place that takes into accounts sequencing depth, bi-sulfite conversion rate, sequencing error rate while identifying DMRs. methylPipe and compEpiTools R packages presents a combined suite of tools including functions for storing, querying, processing, visualization and integrative analysis of (epi)genomics data. Regards, Kamal
[Bioc-devel] compEpiTools and methylPipe
1 message · Kamal