Description Usage Arguments Details Value Author(s) References See Also
View source: R/blockwiseModulesC.R
Calculation of the topological overlap matrix, and the corresponding dissimilarity, from a given adjacency matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  TOMsimilarity(
adjMat,
TOMType = "unsigned",
TOMDenom = "min",
suppressTOMForZeroAdjacencies = FALSE,
useInternalMatrixAlgebra = FALSE,
verbose = 1,
indent = 0)
TOMdist(
adjMat,
TOMType = "unsigned",
TOMDenom = "min",
suppressTOMForZeroAdjacencies = FALSE,
useInternalMatrixAlgebra = FALSE,
verbose = 1,
indent = 0)

adjMat 
adjacency matrix, that is a square, symmetric matrix with entries between 0 and 1
(negative values are allowed if 
TOMType 
a character string specifying TOM type to be calculated. One of 
TOMDenom 
a character string specifying the TOM variant to be used. Recognized values are

suppressTOMForZeroAdjacencies 
Logical: should TOM be set to zero for zero adjacencies? 
useInternalMatrixAlgebra 
Logical: should WGCNA's own, slow, matrix multiplication be used instead of Rwide BLAS? Only useful for debugging. 
verbose 
integer level of verbosity. Zero means silent, higher values make the output progressively more and more verbose. 
indent 
indentation for diagnostic messages. Zero means no indentation, each unit adds two spaces. 
The functions perform basically the same calculations of topological overlap. TOMdist
turns the
overlap (which is a measure of similarity) into a measure of dissimilarity by subtracting it from 1.
Basic checks on the adjacency matrix are performed and missing entries are replaced by zeros.
If TOMType = "unsigned"
, entries of the adjacency matrix are required to lie between 0 and 1;
for TOMType = "signed"
they can be between 1 and 1. In both cases the resulting TOM entries, as
well as the corresponding dissimilarities, lie between 0 and 1.
The underlying C code assumes that the diagonal of the adjacency matrix equals 1. If this is not the case, the diagonal of the input is set to 1 before the calculation begins.
A matrix holding the topological overlap.
Peter Langfelder
Bin Zhang and Steve Horvath (2005) "A General Framework for Weighted Gene CoExpression Network Analysis", Statistical Applications in Genetics and Molecular Biology: Vol. 4: No. 1, Article 17
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