SOFTWARE TOOLS
BIS-SNP - A BISULFITE SPACE GENOTYPER & METHYLATION CALLER
BisSNP is a package based on the Genome Analysis Toolkit (GATK) map-reduce framework for genotyping and accurate DNA methylation calling in bisulfite treated massively parallel sequencing (Bisulfite-seq, NOMe-seq, RRBS and any other bisulfite treated sequencing) with Illumina directional library protocol.
IGV - INTEGRATIVE GENOMICS VIEWER. FAST, EFFICIENT, SCALABLE VISUALIZATION TOOL FOR GENOMICS DATA AND ANNOTATIONS
The Integrative Genomics Viewer (IGV) is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.
EPIGENOME CENTER DATA PORTAL (ECDP)
This scalable portal allows researchers to explore and download their datasets in a secure fashion. From the initial LIMS sample entry (currently using Genologics) through sequencing and downstream analysis on our supercomputing cluster, all characteristics of a sample are parsed and tracked allowing for the presentation of these metrics on a single integrated interface.
A PACKAGE FOR PREDICTING THE DISRUPTIVENESS OF SINGLE NUCLEOTIDE POLYMORPHISMS ON TRANSCRIPTION FACTOR BINDING SITES
We introduce motifbreakR, which allows the biologist to judge in the first place whether the sequence surrounding the polymorphism is a good match, and in the second place how much information is gained or lost in one allele of the polymorphism relative to another. MotifbreakR is both flexible and extensible over previous offerings; giving a choice of algorithms for interrogation of genomes with motifs from public sources that users can choose from; these are 1) a weighted-sum probability matrix, 2) log-probabilities, and 3) weighted by relative entropy. MotifbreakR can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within Bioconductor (currently there are 22).
STATEHUB-STATEPAINTR: RULES-BASED CHROMATIN STATE ANNOTATIONS
Genome annotation is critical to understand the function of disease variants, especially for clinical applications. To meet this need there are segmentations available from public consortia reflecting varying unsupervised approaches to functional annotation based on epigenetics data, but there remains a need for transparent, reproducible, and easily interpreted genomic maps of the functional biology of chromatin. We introduce a new methodological framework for defining a combinatorial epigenomic model of chromatin state on a web database, StateHub.
HICAGE: AN R PACKAGE FOR LARGE-SCALE ANNOTATION AND VISUALIZATION OF 3C-BASED GENOMIC DATA
Chromatin interactions measured by the 3C-based family of next generation technologies are becoming increasingly important for measuring the physical basis for regulatory interactions between different classes of functional domains in the genome. Software is needed to streamline analyses of these data and integrate them with custom genome annotations, RNA-seq, and gene ontologies. We introduce a new R package compatible with Bioconductor---Hi-C Annotation and Graphics Ensemble (HiCAGE)---to perform these tasks with minimum effort. In addition, the package contains a shiny/R web app interface to provide ready access to its functions.
ENHANCER LINKING BY METHYLATION EXPRESSION RELATIONSHIPS (ELMER)
ELMER is designed to combine DNA methylation and gene expression data from human tissues to infer multi-level cis-regulatory networks. It uses DNA methylation to identify enhancers, and correlates enhancer state with expression of nearby genes to identify one or more transcriptional targets. Transcription factor (TF) binding site analysis of enhancers is coupled with expression analysis of all TFs to infer upstream regulators. This package can be easily applied to TCGA public available cancer data sets and custom DNA methylation and gene expression data
GENAVi
GENAVi (Gene Expression Normalization Analysis and Visualization) is a GUI based web application that provides a user-friendly platform to normalize gene expression data, cluster samples based on expression, perform differential expression analysis and visualize results. Our software implements commonly used R packages that represent the “gold standard” for RNA-seq analysis. With GENAVi, users can perform an entire analysis pipeline on the breast and ovarian cancer data provided within the application as well as upload their own expression matrix.
