Package 'WGCNA' - Laboratory Web Sites - UCLA

24 checkAdjMat
blocks
blockOrder
MEsOK
if input blocks was given, its copy; otherwise a vector of length equal number
of genes giving the block label for each gene. Note that block labels are not
necessarilly sorted in the order in which the blocks were processed (since we do
not require this for the input blocks). See blockOrder below.
a vector giving the order in which blocks were processed and in which blockGenes
above is returned. For example, blockOrder[1] contains the label of the
first-processed block.
logical indicating whether the module eigengenes were calculated without errors.
Note
If the input dataset has a large number of genes, consider carefully the maxBlockSize as it significantly
affects the memory footprint (and whether the function will fail with a memory allocation
error). From a theoretical point of view it is advantageous to use blocks as large as possible; on the
other hand, using smaller blocks is substantially faster and often the only way to work with large
numbers of genes. As a rough guide, it is unlikely a standard desktop computer with 4GB memory
or less will be able to work with blocks larger than 8000 genes.
Author(s)
Peter Langfelder
References
Bin Zhang and Steve Horvath (2005) "A General Framework for Weighted Gene Co-Expression
Network Analysis", Statistical Applications in Genetics and Molecular Biology: Vol. 4: No. 1,
Article 17
See Also
goodSamplesGenes for basic quality control and filtering;
adjacency, TOMsimilarity for network construction;
hclust for hierarchical clustering;
cutreeDynamic for adaptive branch cutting in hierarchical clustering dendrograms;
mergeCloseModules for merging of close modules.
checkAdjMat
Check adjacency matrix
Description
Checks a given matrix for properties that an adjacency matrix must satisfy.
Usage
checkAdjMat(adjMat, min = 0, max = 1)