Description Details Author(s) References
Mining gene expression profiles has proven valuable for identifying signatures serving as surrogates of cancer phenotypes. However, the similarities of such signatures across different cancer types have not been strong enough to conclude that they represent a universal biological mechanism shared among multiple cancer types. The Attractor Metagenes Finding Algorithm is a computational method for generating signatures using an iterative process that converges to one of several precise attractors defining signatures representing biomolecular events, such as cell transdifferentiation or the presence of an amplicon.
Package: | cafr |
Version: | 0.3 |
Date: | 2013-03-18 |
Depends: | R (>= 2.13) |
License: | GPL (>= 2) |
Built: | R 2.15.2; x86_64-unknown-linux-gnu; 2013-03-18 21:16:10 UTC; unix |
Index:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | Attractor Class '"Attractor"'
AttractorSet Class '"AttractorSet"'
attractorScanning Find all attractors in the dataset
attractorScanningGL Find all genomically-localized attractors in
the dataset
clusterAttractors Cluster attractors from difference datasets
createMetageneSpace Create metagene-level expression matrix using a
given list
findAttractor Finding attractor using the seed gene
findGLAttractor Finding genomically-localized attractor using
the seed gene
getCorr Functions to calculate correlation coefficient
getMI Functions to calculate mutual information
loadExpr Load txt files into matrix or dataframe
parAttractorScanning Parallelized attractor scanning function
probeSummarization Gene-level expression summarization
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Cheng, Wei-Yi <wc2302@columbia.edu>
Wei-Yi Cheng, Tai-Hsien Ou Yang and Dimitris Anastassiou, Biomolecular events in cancer revealed by attractor metagenes, PLoS Computational Biology, Vol. 9, Issue 2, February 2013.
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