connectivityScore {PharmacoGx} | R Documentation |
A function for finding the connectivity between two signatures, using either the GSEA method based on the KS statistic, or the gwc method based on a weighted spearman statistic. The GSEA analysis is implemented in the piano package.
connectivityScore( x, y, method = c("gsea", "fgsea", "gwc"), nperm = 10000, nthread = 1, gwc.method = c("spearman", "pearson"), ... )
x |
A |
y |
A |
method |
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nperm |
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nthread |
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gwc.method |
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... |
Additional arguments passed down to gsea and gwc functions |
numeric
a numeric vector with the score and the p-value associated
with it
F. Pozzi, T. Di Matteo, T. Aste, 'Exponential smoothing weighted correlations', The European Physical Journal B, Vol. 85, No 6, 2012. DOI: 10.1140/epjb/e2012-20697-x
Varemo, L., Nielsen, J. and Nookaew, I. (2013) Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods. Nucleic Acids Research. 41 (8), 4378-4391. doi: 10.1093/nar/gkt111
xValue <- c(1,5,23,4,8,9,2,19,11,12,13) xSig <- c(0.01, 0.001, .97, 0.01,0.01,0.28,0.7,0.01,0.01,0.01,0.01) yValue <- c(1,5,10,4,8,19,22,19,11,12,13) ySig <- c(0.01, 0.001, .97,0.01, 0.01,0.78,0.9,0.01,0.01,0.01,0.01) xx <- cbind(xValue, xSig) yy <- cbind(yValue, ySig) rownames(xx) <- rownames(yy) <- c('1','2','3','4','5','6','7','8','9','10','11') data.cor <- connectivityScore(xx,yy,method='gwc', gwc.method='spearman', nperm=300)