Returns the pairwise similarity matrix from a multiple alignment.
Usage
similarityMatrix(object)
# S4 method for class 'ConsortiumMetabolismAlignment'
similarityMatrix(object)Arguments
- object
A ConsortiumMetabolismAlignment object of type
"multiple".
Methods (by class)
similarityMatrix(ConsortiumMetabolismAlignment): Similarity matrix from a ConsortiumMetabolismAlignment. For multiple alignments this is the symmetric n x n pairwise matrix; for database search alignments it is a 1 x n row vector of the query's scores against each database member.
Examples
cm1 <- synCM("comm_1", n_species = 3, max_met = 5)
cm2 <- synCM("comm_2", n_species = 4, max_met = 6)
cms <- ConsortiumMetabolismSet(cm1, cm2, name = "test")
#>
#> ── Creating CMS "test" ─────────────────────────────────────────────────────────
#> ℹ Validating 2 <ConsortiumMetabolism> objects
#> ✔ Validating 2 <ConsortiumMetabolism> objects [11ms]
#>
#> ℹ Collecting metabolites from 2 consortia
#> ✔ Collecting metabolites from 2 consortia [29ms]
#>
#> ℹ Re-indexing 6 unique metabolites
#> ✔ Re-indexing 6 unique metabolites [39ms]
#>
#> ℹ Expanding 2 binary matrices to 6-dimensional space
#> ✔ Expanding 2 binary matrices to 6-dimensional space [24ms]
#>
#> ℹ Computing 6 x 6 levels matrix
#> ✔ Computing 6 x 6 levels matrix [24ms]
#>
#> ℹ Computing pairwise overlap (1 pairs via crossprod)
#> ✔ Computing pairwise overlap (1 pairs via crossprod) [22ms]
#>
#> ℹ Assembling pathway data from 2 consortia
#> ✔ Assembling pathway data from 2 consortia [29ms]
#>
#> ℹ Building dendrogram from 2 x 2 dissimilarity matrix
#> ✔ Building dendrogram from 2 x 2 dissimilarity matrix [21ms]
#>
#> ℹ Extracting dendrogram node positions
#> ✔ Extracting dendrogram node positions [23ms]
#>
#> ℹ Collecting 2 consortium graphs
#> CMS "test" created: 2 consortia, 6 metabolites (0.2s)
#> ✔ Collecting 2 consortium graphs [77ms]
#>
cma <- align(cms)
#> Computing multiple alignment for 2 consortia using "FOS".
similarityMatrix(cma)
#> comm_1 comm_2
#> comm_1 1 0
#> comm_2 0 1