calculateSimMatrix Calculate the score similarity matrix between terms

calculateSimMatrix(
  x,
  orgdb,
  keytype = "ENTREZID",
  semdata = GOSemSim::godata(annoDb = orgdb, ont = ont, keytype = keytype),
  ont = c("BP", "MF", "CC"),
  method = c("Resnik", "Lin", "Rel", "Jiang", "Wang"),
  include_terms_without_IC = FALSE
)

Arguments

x: vector of GO terms
orgdb: one of org.* Bioconductor packages (the package name, or the package itself)
keytype: keytype passed to AnnotationDbi::keys to retrieve GO terms associated to gene ids in your orgdb
semdata: object with prepared GO DATA for measuring semantic similarity
ont: ontology. One of c("BP", "MF", "CC")
method: distance method. One of the supported methods by GOSemSim: c("Resnik", "Lin", "Rel", "Jiang", "Wang")
include_terms_without_IC: whether to include terms for which there's no Information Content in OrgDb. NOTE: Including them can mess up with the algorithm that aggregates the distances. Default: FALSE.

Value

a square matrix with similarity scores between terms

Details

All similarity measures available are those implemented in the [GOSemSim package](https://www.bioconductor.org/packages/release/bioc/html/GOSemSim.html), namely the Resnik, Lin, Relevance, Jiang and Wang methods. See the [Semantic Similarity Measurement Based on GO](https://www.bioconductor.org/packages/release/bioc/vignettes/GOSemSim/inst/doc/GOSemSim.html#semantic-similarity-measurement-based-on-go) section from the GOSeSim documentation for more details.

Examples

go_analysis <- read.delim(system.file("extdata/example.txt", package="rrvgo"))
simMatrix <- calculateSimMatrix(go_analysis$ID, orgdb="org.Hs.eg.db", ont="BP", method="Rel")
#> 
#> preparing gene to GO mapping data...
#> preparing IC data...