GLMnetwork infers a network from RNA-seq expression with the
log-linear Poisson graphical model of (Allen and Liu, 2012).
a n x p matrix of RNA-seq expression (numeric matrix or data frame)
a sequence of decreasing positive numbers to control the
regularization (numeric vector). Default to
logical value to normalize predictors in the log-linear
Poisson graphical model. If
lambdas are null the default sequence of
glmnet for the first model (the one with the first
count as the target) is used.
S3 object of class
GLMnetwork: a list consisting of
lambda regularization parameters used for LLGM path(vector)
path a list having the same length than
contains the estimated coefficients (in a matrix) along the path
Alyssa Imbert, firstname.lastname@example.org
Nathalie Vialaneix, email@example.com
Allen, G. and Liu, Z. (2012) A log-linear model for inferring genetic networks from high-throughput sequencing data. In Proceedings of IEEE International Conference on Bioinformatics and Biomedecine (BIBM).
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