Disease variants alter transcription factor levels and methylation of their binding sites.

Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions.

Identification of context-dependent expression quantitative trait loci in whole blood.

Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease.

RCytoscape: tools for exploratory network analysis.

Background: Biomolecular pathways and networks are dynamic and complex, and the perturbations to them which cause disease are often multiple, heterogeneous and contingent. Pathway and network visualizations, rendered on a computer or published on paper, however, tend to be static, lacking in detail, and ill-equipped to explore the variety and quantities of data available today, and the complex causes we seek to understand.

Results: RCytoscape integrates R (an open-ended programming environment rich in statistical power and data-handling facilities) and Cytoscape (powerful network visualization and analysis software).

CytoscapeRPC: a plugin to create, modify and query Cytoscape networks from scripting languages.

Summary: CytoscapeRPC is a plugin for Cytoscape which allows users to create, query and modify Cytoscape networks from any programming language which supports XML-RPC. This enables them to access Cytoscape functionality and visualize their data interactively without leaving the programming environment with which they are familiar.

Availability: Install through the Cytoscape plugin manager or visit the web page: http://wiki.

Inferring combinatorial association logic networks in multimodal genome-wide screens.

Motivation: We propose an efficient method to infer combinatorial association logic networks from multiple genome-wide measurements from the same sample. We demonstrate our method on a genetical genomics dataset, in which we search for Boolean combinations of multiple genetic loci that associate with transcript levels.

Results: Our method provably finds the global solution and is very efficient with runtimes of up to four orders of magnitude faster than the exhaustive search.

Identification of networks of co-occurring, tumor-related DNA copy number changes using a genome-wide scoring approach.

Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells.

Co-occurrence analysis of insertional mutagenesis data reveals cooperating oncogenes.

Motivation: Cancers are caused by an accumulation of multiple independent mutations that collectively deregulate cellular pathways, e.g. such as those regulating cell division and cell-death.