VisRseq is a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise.
VisRseq framework provides an extendable collection of R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and Bioconductor. To address the interactivity limitation inherent in R, several native apps are built into the framework that provide interactive exploration and brushing operations as well as an integrated genome browser. All apps can be chained together to create more powerful analysis workflows.
For more information, user guides and downloads, visit the VisRseq project web site.
ALEA is a computational toolbox for allele-specific (AS) epigenomics analysis.
ALEA incorporates allelic variation data within existing resources, allowing for the identification of significant associations between epigenetic modifications and specific allelic variants in human and mouse cells. ALEA provides a customizable pipeline of command line tools for AS analysis of next-generation sequencing data (ChIP-seq, RNA-seq, etc.) that takes the raw sequencing data and produces separate allelic tracks ready to be viewed on genome browsers.
For more information, user guides and downloads, visit the Alea project web site.
ChAsE (Chromatin Analysis and Exploration) is a cross platform desktop application that provides an interactive graphical interface for analysis of epigenomic data.
Chase allows users to interactively explore and analyze epigenomic data through an integrated clustering and heat map interface. Features include:
- Exploration and visualization of the data using an interactive heat map and plot interface
- Clustering the data automatically or manually by sorting and brushing the heat map
- Exporting results for downstream analysis or as high quality images for publications
For more information, tutorial video and downloads, visit the ChAsE project web site.
Spark is an interactive clustering and visualization tool.
Spark enables exploration of genome-wide data. It requires two inputs: (i) one or more data tracks, and (ii) a set of genome coordinates of interest. Sparks then extracts data from the input tracks at the specified regions of interest and clusters them. The resulting visualization uses the clusters as a high-level visual guide to the common data patterns in the input data and provides links to gene ontology analysis tools. It also supports the interactive inspection of individual regions within each cluster and connects them to existing genome browser displays, taking advantage of their wealth of annotation and functionality.
For more information including video tutorials and downloads, visit the Spark project web site.
FindER is an analytical analysis tool to study epigenetic modifications and protein-DNA interactions from ChIP-Seq data.
Taking ChIP-Seq and Input DNA alignment files in the BAM format FindER generates regions of enrichment for a given significance (FDR). Currently alignments to human genome (hg19) and mouse reference (mm10), both paired-end and single-end, are supported. Some postprocessing options (e.g. combining closely positioned enriched regions and filtering on the enriched region size) are enabled with FindER. The data set saturation study option is also available with user configurable random partitioning of the sequenced reads.
For more information on FindER and the software download, visit the FindER project page.
Code released by the EDCC/CEMT at GSC for analyzing, managing and publishing epigenomic data. Fork of the EDCC/CEMT contributions to International Human Epigenome Consortium are also independently maintained here.
BAM2WIG is a flexible tool to generate read coverage profile (WIG file) from a BAM file.
BAM2WIG can be used for various types of data, such as whole genome shotgun sequencing (WGSS), RNA-seq, ChIP-seq etc. Data can be pair end (PET) or single end (SET). It allows you to generate DNA fragment coverage profiles for PET data (WGBS, ChIP-seq) and coverage for directionally extended reads for SET ChIP-seq.
The BAM2WIG tool also adjusts chromosome namings so that WIG file is displayable at UCSC. See chromosome resource files:
Download BAM2WIG 1.0.0.
To see a list of options and help for this tool, run it as a jar file:
java -jar ./BAM2WIG-1.0.0.jar