[Bioc-devel] compEpiTools and methylPipe

Kamal kamal.fartiyal84 at gmail.com
Mon Oct 27 16:39:07 CET 2014


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

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