# R/Functions-fromSimilarity.R In WGCNA: Weighted Correlation Network Analysis

```# Functions to perform WGCNA from similarity input.

matrixToNetwork = function(mat,
symmetrizeMethod = c("average", "min", "max"),
signed = TRUE,
min = NULL,
max = NULL,
power = 12,
diagEntry = 1)
{
sm = match.arg(symmetrizeMethod);
if (is.na(sm))
stop("Unrecognized or non-unique 'symmetrizeMethod'.");

mat = as.matrix(mat);

nd = 0
x = try({nd = dim(mat)});
if ( (class(x)=='try-error') | (nd!=2) )
stop("'mat' appears to have incorrect type; must be a 2-dimensional square matrix.");

if (ncol(mat)!=nrow(mat))
stop("'mat' must be a square matrix.");

if (!signed) mat = abs(mat);

if (sm==1) {
mat = (mat + t(mat))/2;
} else if (sm==2) {
mat = pmin(mat, t(mat), na.rm = TRUE);
} else
mat = pmax(mat, t(mat), na.rm = TRUE);

if (is.null(min)) {
min = min(mat, na.rm = TRUE);
} else
mat[mat < min] = min;

if (is.null(max)) {
max = max(mat, na.rm = TRUE);
} else
mat[mat > max] = max;

}

checkSimilarity = function(similarity, min=-1, max=1)
{
}

adjacency.fromSimilarity = function(similarity, type = "unsigned", power = if (type=="distance") 1 else 6)
{
checkSimilarity(similarity);
adjacency(similarity, type = type, power = power, corFnc = "I", corOptions="", distFnc = "I",
distOptions = "");
}

softConnectivity.fromSimilarity=function(similarity, type = "unsigned",
power = if (type == "signed") 15 else 6,
blockSize = 1500, verbose = 2, indent = 0)

{
checkSimilarity(similarity)
softConnectivity(similarity, corFnc = "I", corOptions = "",
type = type, power = power,
blockSize = blockSize, verbose = verbose, indent = indent)
}

pickHardThreshold.fromSimilarity=function (similarity,
RsquaredCut = 0.85, cutVector = seq(0.1, 0.9, by = 0.05),
moreNetworkConcepts=FALSE , removeFirst = FALSE, nBreaks = 10)
{
checkSimilarity(similarity)
pickHardThreshold(similarity, dataIsExpr = FALSE, RsquaredCut =  RsquaredCut, cutVector = cutVector,
moreNetworkConcepts = moreNetworkConcepts, removeFirst = removeFirst,
nBreaks = nBreaks, corFnc = "I", corOptions = "");
}

pickSoftThreshold.fromSimilarity = function (similarity,
RsquaredCut = 0.85, powerVector = c(seq(1, 10, by = 1), seq(12, 20, by = 2)),
removeFirst = FALSE, nBreaks = 10, blockSize = 1000,
moreNetworkConcepts=FALSE, verbose = 0, indent = 0)
{
checkSimilarity(similarity)
pickSoftThreshold(similarity, dataIsExpr = FALSE, RsquaredCut =  RsquaredCut, powerVector = powerVector,
removeFirst = removeFirst, nBreaks = nBreaks,
blockSize = blockSize, networkType = "signed",
moreNetworkConcepts = moreNetworkConcepts,
verbose = verbose, indent = indent);

}
```

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WGCNA documentation built on March 1, 2021, 1:05 a.m.