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ProDiGe specifications

Information


Unique identifier OMICS_18226
Name ProDiGe
Alternative name Prioritization of Disease Genes
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages MATLAB
Computer skills Advanced
Version 0.3
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Jean-Philippe Vert

Publication for Prioritization of Disease Genes

ProDiGe citations

 (7)
library_books

Genetic and functional characterization of disease associations explains comorbidity

2017
Sci Rep
PMCID: 5524755
PMID: 28740175
DOI: 10.1038/s41598-017-04939-4

[…] sess the significance of the genetic overlap between them (Figure , Supplementary Methods) and the number of significant DDAs increases to 8,012 (Figure ). Moreover, we demonstrate that network-based prioritization of disease genes can unravel disease relationships even when two diseases do not have seeds in common (see Figure  in Supplementary Methods).Next, we ask whether network-based expansion […]

library_books

Brain transcriptome atlases: a computational perspective

2016
PMCID: 5406417
PMID: 27909802
DOI: 10.1007/s00429-016-1338-2

[…] chment of autism-candidate genes among genes with correlated temporal patterns to CHD8 in the BrainSpan atlas. Fig. 3 Gene co-expression can serve as a very powerful tool for in silico prediction and prioritization of disease genes, by identifying genes with similar expression pattern to known disease genes. Piro et al. () described a candidate gene prioritization method using the Allen Mouse Brai […]

library_books

Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes

2016
BMC Genomics
PMCID: 5070370
PMID: 27756223
DOI: 10.1186/s12864-016-3108-1

[…] targets which could advance the discovery of drugs for the disease []. Lately, network-based methods integrating properties from protein-protein interaction (PPI) networks, have been widely used for prioritization of disease genes and finding an association between the genes and the diseases. Liu and Xie, 2013 integrated network properties from PPI networks, and sequence and functional properties […]

library_books

Human protein interaction networks across tissues and diseases

2015
Front Genet
PMCID: 4541328
PMID: 26347769
DOI: 10.3389/fgene.2015.00257

[…] s. Magger et al. () showed that the usage of tissue interactomes, created from a generic interactome by removing or penalizing interactions involving non-expressed proteins, considerably improved the prioritization of disease genes. Li et al. () assessed tissue interactomes weighted by DNA methylation data, and showed that they enhance prediction of disease genes. Barshir et al. () focused on gene […]

library_books

EvoTol: a protein sequence based evolutionary intolerance framework for disease gene prioritization

2014
Nucleic Acids Res
PMCID: 4357693
PMID: 25550428
DOI: 10.1093/nar/gku1322

[…] larly used to evaluate excesses of mutation in gene sets and evaluate the significance for individual genes.Here we present an alternative method to RVIS () and the constraint score () for gene-level prioritization of disease genes. Uniquely, our method, EvoTol, combines genic intolerance with evolutionary conservation of whole protein sequences or their constituent protein domains to prioritize d […]

library_books

Comparative Analysis of Human Tissue Interactomes Reveals Factors Leading to Tissue Specific Manifestation of Hereditary Diseases

2014
PLoS Comput Biol
PMCID: 4055280
PMID: 24921629
DOI: 10.1371/journal.pcbi.1003632

[…] a filter for constructing tissue interactomes (e.g., , , –). The effectiveness of filtered tissue interactomes was demonstrated in two recent studies, which showed that they considerably improve the prioritization of disease genes relative to an unfiltered global interactome , .The interactomes of the different tissues had common features. First, the majority of their genes were common to 14 or m […]

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ProDiGe institution(s)
Centre for Computational Biology, Mines ParisTech, Fontainebleau, France; Institut Curie, Paris, France; U900, INSERM, Paris, France; CREST, INSEE, Malakoff, France
ProDiGe funding source(s)
Supported by ANR grants ANR-07-BLAN-0311-03 and ANR-09-BLAN- 0051-04.

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