Comparative interactomics with Funcoup 2.0

Abstract

FunCoup (http://FunCoup.sbc.su.se) is a database that maintains and visualizes global gene/protein networks of functional coupling that have been constructed by Bayesian integration of diverse high-throughput data. FunCoup achieves high coverage by orthology-based integration of data sources from different model organisms and from different platforms. We here present release 2.0 in which the data sources have been updated and the methodology has been refined. It contains a new data type Genetic Interaction, and three new species: chicken, dog and zebra fish. As FunCoup extensively transfers functional coupling information between species, the new input datasets have considerably improved both coverage and quality of the networks. The number of high-confidence network links has increased dramatically. For instance, the human network has more than eight times as many links above confidence 0.5 as the previous release. FunCoup provides facilities for analysing the conservation of subnetworks in multiple species. We here explain how to do comparative interactomics on the FunCoup website.

The human gene connectome as a map of short cuts for morbid allele discovery

“…Instead, the aim is to automate the ranking of the polymorphic genes according to their distance and specific route (rather than the large shared network) to the known, experimentally validated core gene. We show here that the current state-of-the-art methods String (7), FunCoup (8), and HumanNet (9), although excellent for polygenic research, are not optimized for monogenic phenotype/disease research as, in most cases, they cannot predict the single biologically plausible distance and route between a pair of genes that are not directly connected (Figs. S2-S7, Materials and Methods).…”

“…The abundance of high-throughput data provides an opportunity to test this hypothesis of pathogenesis and pathway homogeneity (5,6). However, it is often almost impossible to detect biological links between very small numbers of genes with state-of-the-art programs, such as String (7), FunCoup (8), and HumanNet (9), unless they are predicted to be directly connected in a pathway. These programs provide estimates for direct connections or for the extended network shared by two given genes from the same pathway, rather than the specific pathway (i.e., route) between any two given genes of interest.…”

Protein–protein interactions and genetic diseases: The interactome

“…A non-exhaustive list includes InWeb 19 , GeneMANIA 53 , Funcoup 17 , I2D 54 , PINA 55 , ConsensusPathDB 56 , STRING 48 , and IMEx consortium 9 , and mentha 57 …”

“…Rossin et al, 13 developed disease association protein-protein link evaluator (DAPPLE, www.broadinstitute.org/mpg/dapple/) to show that proteins encoded in Crohn’s disease and rheumatoid arthritis physically interact to suggest specific biological processes and candidate genes in incriminated loci. This algorithm has become widely used in the genetics community and has for example also been used to analyze data from inflammatory bowel diseases 16 and type 2 diabetes 17 (Figure 4). Similarly, Bergholdt et al, integrated protein-protein interactions and GWAS data to identify candidate genes in type 1 diabetes 15 .…”

MaxLink: network-based prioritization of genes tightly linked to a disease seed set

“…known to be involved in a particular disease or condition. The web service is run using default or user-specified values for the following parameters: 'Query network' (default: Homo sapiens)-one of the 11 currently available model organism networks in FunCoup 3.0 (Schmitt et al, 2014); 'Network confidence threshold' (default: 0.75)-a confidence threshold for the links in the underlying network, known as pfc in FunCoup (Alexeyenko et al, 2011);and the 'Hypergeometric Cutoff' (default 0.1)-a hypergeometric probability cutoff to ensure that identified genes are statistically enriched in connections to the query set. These parameters can be altered according to user guidelines found at the MaxLink Web site.…”