# Some code from the OneHandClapping package
# to enable the use of hclust in a S4 class.
# dummy class because 'hclust' is S3 class
setClass("hclust",contains="list")
##|| The pepcor class will hold all the results from peptide network calculations
##|| Version of procona that built the network
##|| the name of the network
##|| the samples used to make the network
##|| the adjacency matrix
##|| the topological overlap matrix
##|| the names of the peptides, usually AMT IDs
##|| the original dendrogram
##|| The cuts from dynamic tree cut
##|| the module eigenvectors from dynamic cut
##|| module eigen-peptides
##|| the merged colors
##|| the color order
##|| the power used in the model
##|| the adjacency matrix is signed or unsigned
##|| the results of the permutation test
setClass("proconaNet",
representation(
proconaVersion = "character",
networkName="character",
samples="character",
adj = "matrix",
TOM = "matrix",
peptides = "character",
pepTree = "hclust",
dynamicColors = "numeric",
MEs = "data.frame",
mergedMEs = "data.frame",
mergedColors = "numeric",
colorOrder = "character",
power= "numeric",
networkType= "character",
permtest="matrix"
),
prototype(
proconaVersion="0",
networkName="ProCoNA Network",
samples=c("a","b","c"),
adj=matrix(data=0, ncol=3, nrow=3),
TOM=matrix(data=0, ncol=3, nrow=3),
peptides=c("d","e","f"),
pepTree= hclust(d=dist(matrix(c(1,1,1,1)))),
dynamicColors=c(-1,-1,-1),
MEs=data.frame(A=c(0,0,0), B=c(0,0,0), C=c(0,0,0)),
mergedMEs=data.frame(A=c(0,0,0), B=c(0,0,0), C=c(0,0,0)),
mergedColors=c(-1,-1,-1),
colorOrder=c(""),
power=1,
networkType="signed",
permtest=matrix()
)
#validity = check_proconaNet
)
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