Mining tissue specificity, gene connectivity and disease association to reveal a set of genes that modify the action of disease causing genes

doi:10.1186/1756-0381-1-8

BioData Mining

Volume 1

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Mining tissue specificity, gene connectivity and disease association to reveal a set of genes that modify the action of disease causing genes

Antonio Reverter , Aaron Ingham and Brian P Dalrymple

Computational and Systems Biology, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St. Lucia, Brisbane, Queensland 4067, Australia

author email corresponding author email

BioData Mining 2008, 1:8doi:10.1186/1756-0381-1-8


Published:	19 September 2008

Additional files

Additional file 1:

Additional Table 1: The set of 15,050 genes. List of 15,050 genes included in the analyses. For each gene, the number of tissues (out of 32) in which the gene is being expressed, its average expression, disease association and connectivity structure is provided.

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Additional file 2:

Additional Table 2: Set of 112 guilt-by-association genes. List of 112 genes not associated with disease according to OMIM yet with high connectivity with disease-associated genes. For each gene, the proportion of disease genes among connectors and polymorphism or differential expression associated with disease along with the relevant literature reference is provided.

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