Description Usage Arguments Value Author(s) References See Also Examples
GLMnetToGraph
combines the m inferred networks, obtained from m
imputed datasets, into a single stable network or convert a matrix of
coefficients of a GLM model into a network (non zero coefficients are
converted to edges)
1 | GLMnetToGraph(object, threshold = 0.9)
|
object |
an object of class |
threshold |
the percentage of times, among the m imputed networks, that
an edge has to be predicted to be in the final network. Used only for objects
of class |
an 'igraph' object. See igraph
Alyssa Imbert, alyssa.imbert@gmail.com
Nathalie Vialaneix, nathalie.vialaneix@inrae.fr
Imbert, A., Valsesia, A., Le Gall, C., Armenise, C., Lefebvre, G. Gourraud, P.A., Viguerie, N. and Villa-Vialaneix, N. (2018) Multiple hot-deck imputation for network inference from RNA sequencing data. Bioinformatics. doi: 10.1093/bioinformatics/btx819.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | data(lung)
data(thyroid)
nobs <- nrow(lung)
miss_ind <- sample(1:nobs, round(0.2 * nobs), replace = FALSE)
lung[miss_ind, ] <- NA
lung <- na.omit(lung)
lambdas <- 4 * 10^(seq(0, -2, length = 10))
## Not run:
lung_hdmi <- imputedGLMnetwork(lung, thyroid, sigma = 2, lambdas = lambdas,
m = 10, B = 5)
lung_net <- GLMnetToGraph(lung_hdmi, 0.75)
lung_net
plot(lung_net)
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.