The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various aspects of the pathway topology have been proposed. These topology-based methods, sometimes referred to as "third generation," have the potential to better model the phenomena described by pathways.
Performs peak finding and downstream data analysis for next-generation sequencing analysis. HOMER affords several tools and methods to make use of ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and other types of functional genomics sequencing data sets. This software offers support to UCSC visualization, peaks annotation, quantification of transcripts and repeats or differential features, enrichment and expression.
Allows users to obtain biological features/meaning associated with large gene or protein lists. DAVID can determine gene-gene similarity, based on the assumption that genes sharing global functional annotation profiles are functionally related to each other. It groups related genes or terms into functional groups employing the similarity distances measure. This tool takes into account the redundant and network nature of biological annotation contents.
Offers different tools for testing gene ontology (GO) terms according to the topology of the GO graph. TopGO allows using several test statistics and methods for remove local similarities and dependencies between GO terms.
Accelerates discovery research with systems biology content, analytics, and expertise. MetaCore is an integrated software suite for functional analysis of Next Generation Sequencing (NGS), gene expression, copy number variation (CNV), metabolic, proteomics, microRNA, and screening data. This method is based on a high-quality, manually-curated database of molecular interactions, molecular pathways, gene-disease associations, chemical metabolism and toxicity information.
Permits the management, information retrieval, organization, visualization and statistical analysis of large sets of genes. WebGestalt integrates functional enrichment analysis and information visualization. It supports about 12 organisms, more than 320 gene identifiers from various databases and technology platforms, and about 151 000 functional categories from public databases and computational analyses.
A web-based tool for the ontological analysis of large lists of genes. It can be used to determine biological annotations or combinations of annotations that are significantly associated to a list of genes under study with respect to a reference list. As well as single annotations, this tool allows users to simultaneously evaluate annotations from different sources, for example Biological Process and Cellular Component categories of Gene Ontology.
Conducts statistical analysis for over-representation of Gene Ontology (GO) terms in sets of genes or proteins derived from an experiment. Ontologizer implements the standard approach to statistical analysis based on the one-sided Fisher's exact test and topology-based algorithms. It provides multiple-testing correction procedures. This tool allows the visualization of data as a graph including all significantly over-represented GO terms.