Description Usage Arguments Value Examples
generate_edge_weight
computes differential gene co-expression
(i.e., the change of gene co-expression between case and control samples) to
infer the edge weight of PPI network. generate_edge_weight
is
generally called by generate_graph
. Typically users do not need
to call it.
1 | generate_edge_weight(expr1, expr2, network, geneweight)
|
expr1 |
A data frame containing gene expression data from case samples. The first column is gene identifier (should be coordinate with the node symbol used in PPI |
expr2 |
A data frame containing gene expression data from control samples. The first column should be the same as expr1 |
network |
A data frame containing a symbolic edge list of the PPI network |
geneweight |
A data frame containing two columns: the first is unique gene identifier (should be coordinate with the node symbol used in PPI); the second is gene-based p-value derived from GWAS |
A co-expression matrix is returned
1 2 3 4 | ## Not run:
edgeweight <- generate_edge_weight(expr1, expr2, network, geneweight)
## End(Not run)
|
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