Difference between revisions of "Catapult"

From Marcotte Lab
Jump to: navigation, search
 
(6 intermediate revisions by 2 users not shown)
Line 1: Line 1:
This is the homepage for Catapult. Here we provide:
+
Catapult is a computer algorithm for associating new genes with traits, phenotypes, and diseases. Catapult leverages hundreds of thousands of known individual gene-phenotype associations from humans, mice, yeast, ''Arabidopsis'', and ''C. elegans'', and interprets them with the aid of a genome-scale functional network of human genes ([http://www.functionalnet.org/humannet/ HumanNet]) in a graph-based formalism in order to rank new candidate genes for diseases/traits of interest.  This is the homepage for Catapult. Here we provide:
  
* The [http://www.cs.utexas.edu/~naga86/research/linkPrediction/biasedSVMSpeciesBagging0109BioInfo/predictions.html predictions] for all the OMIM diseases used.
+
* The [http://www.cs.utexas.edu/~naga86/research/catapult/predictions.html predictions] for all the OMIM diseases used.
 
* A [http://www.cs.utexas.edu/~naga86/research/geneRecommender/ query interface], where you can submit your own gene lists and have the results emailed to you.
 
* A [http://www.cs.utexas.edu/~naga86/research/geneRecommender/ query interface], where you can submit your own gene lists and have the results emailed to you.
* The project [http://www.marcottelab.org/users/mblom/catapult/WeightedWalks1.0.zip source code], if you want to test it all yourself.
+
* The project [http://www.cs.utexas.edu/~naga86/research/catapult/CATAPULT.zip source code], if you want to test it all yourself.
 +
* All [http://www.marcottelab.org/paper-pdfs/genes_phenotypes.txt gene-disease predictions] in a 300MB tab-delimited text file (or .zipped 120MB version [http://www.marcottelab.org/paper-pdfs/genes_phenotypes.zip here]).  Rows represent human genes, indicating gene names in column 1 as NCBI Entrez genome/Locus link ID numbers. Columns represent human diseases or mouse phenotypes. Entries represent computed scores for gene-trait associations, where larger values indicate more likely associations.  All values are scaled, such that sorting by values in a given column allows one to find the most likely genes for that disease, and sorting by values in a given row allows one to find the most likely linked traits for a given gene (obvious caveats being that the diseases/genes must be represented in this table, and the associations are subject to the reach and quality of the predictions captured by CATAPULT.)
 +
 
 +
Citation:  Singh-Blom UM, Natarajan N, Tewari A, Woods JO, Dhillon IS, et al. (2013) Prediction and Validation of Gene-Disease Associations Using Methods Inspired by Social Network Analyses. PLoS ONE 8(5): e58977. doi:10.1371/journal.pone.0058977.

Latest revision as of 12:47, 17 April 2014

Catapult is a computer algorithm for associating new genes with traits, phenotypes, and diseases. Catapult leverages hundreds of thousands of known individual gene-phenotype associations from humans, mice, yeast, Arabidopsis, and C. elegans, and interprets them with the aid of a genome-scale functional network of human genes (HumanNet) in a graph-based formalism in order to rank new candidate genes for diseases/traits of interest. This is the homepage for Catapult. Here we provide:

  • The predictions for all the OMIM diseases used.
  • A query interface, where you can submit your own gene lists and have the results emailed to you.
  • The project source code, if you want to test it all yourself.
  • All gene-disease predictions in a 300MB tab-delimited text file (or .zipped 120MB version here). Rows represent human genes, indicating gene names in column 1 as NCBI Entrez genome/Locus link ID numbers. Columns represent human diseases or mouse phenotypes. Entries represent computed scores for gene-trait associations, where larger values indicate more likely associations. All values are scaled, such that sorting by values in a given column allows one to find the most likely genes for that disease, and sorting by values in a given row allows one to find the most likely linked traits for a given gene (obvious caveats being that the diseases/genes must be represented in this table, and the associations are subject to the reach and quality of the predictions captured by CATAPULT.)

Citation: Singh-Blom UM, Natarajan N, Tewari A, Woods JO, Dhillon IS, et al. (2013) Prediction and Validation of Gene-Disease Associations Using Methods Inspired by Social Network Analyses. PLoS ONE 8(5): e58977. doi:10.1371/journal.pone.0058977.