findGLAttractor: Finding genomically-localized attractor using the seed gene
In weiyi-bitw/cafr: Attractor Metagenes Finding Algorithm

Description Usage Arguments Details Value Author(s) References See Also Examples

Find a converged genomically-localized attractor based on the seed gene provided.

1	findGLAttractor(data,seed, genome, alpha=(2:12)/2, windowSize = 50, maxIter = 100, epsilon=1E-14, bin=6, so=3, score.position=5, num.output=10, negateMI=TRUE, verbose=TRUE)

`data`	An expression matrix with genes in the rows, samples in the columns.
`seed`	The gene symbol of the seed gene.
`genome`	A matrix with genome information. The rownames of the matrix must contains gene symbols in their genomical order. See `data(genome)` for an example.
`alpha`	A vector of exponents to try for convergence.
`windowSize`	Number of genes to be filtered in, centered at the seed gene.
`maxIter`	Max number of iterations.
`epsilon`	Threshold of convergence.
`bin`	Number of bins used when estimate mutual information (default=6).
`so`	Spline order used when estimate mutual information (default=3).
`score.position`	Which rank in the attractor will be used as the strength. (default=5)
`num.output`	Number of genes to include in the attractor.
`negateMI`	When `TRUE`, negate the mutual information if the two vectors have negative momentum.
`verbose`	When `TRUE`, it will show the top 20 genes of the metagene in each iteration.

The genomically-localized attractor usually points to an amplicon or delecon that contains several genes being amplified or deleted simultaneously. Such amplification and deletion within the region reflects on the co-expression of genes in the neighborhood. findGLAttractor performs a mini-scaled attractorScanningGL to find the most prominent genomically-localized attractor in the region of the seed gene. It uses the same algorithm as findAttractor, but restricts the gene space to the neighborhood of the seed gene defined by the windowSize. The significance (or strength) of an attractor is defined by the MI of the score.position-th gene. Default is the fifth-highest MI in the attractor. The function tries all the possible exponents defined in alpha and finds the best one that gives highest score.position-th MI. It then compares all the converged attractors using the seeds in the neighborhood and finds the one with the highest strength.

Returns a vector of MIs of the top genes with the converged metagene. If the process does not converge within the maximum number of iteration assigned, it will return NULL. Each column name of the matrix is the seed used to generate the attractor.

Wei-Yi Cheng

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.

findAttractor, attractorScanning,attractorScanningGL

# Load the toy dataset extracted from TCGA OV data
data(ov)

# Load the genome information
data(genome)

# find a genomically localized attractor in the neighborhood of PUF60 (8q24.3)
seed <- "PUF60"
a <- findGLAttractor(ov, seed, genome)

# display the top 10 genes in the attractor
print(a)