parGOSim: Protein/DNA Sequence Similarity Calculation based on Gene...

In BioMedR: Generating Various Molecular Representations for Chemicals, Proteins, DNAs/RNAs and Their Interactions

Description

Protein/DNA Sequence Similarity Calculation based on Gene Ontology (GO) Similarity

Usage

parGOSim(golist, type = c("go", "gene"), ont = "MF", organism = "human",
  measure = "Resnik", combine = "BMA")

Arguments

golist	A character vector, each component contains a character vector of GO terms or one Entrez Gene ID.
type	Input type of golist, 'go' for GO Terms, 'gene' for gene ID.
ont	Default is 'MF', could be one of 'MF', 'BP', or 'CC' subontologies.
organism	Default is 'human', could be one of 'anopheles', 'arabidopsis', 'bovine', 'canine', 'chicken', 'chimp', 'coelicolor', 'ecolik12', 'ecsakai', 'fly', 'human', 'malaria', 'mouse', 'pig', 'rat', 'rhesus', 'worm', 'xenopus', 'yeast' or 'zebrafish'.
measure	Default is 'Resnik', could be one of 'Resnik', 'Lin', 'Rel', 'Jiang' or 'Wang'.
combine	Default is 'BMA', could be one of 'max', 'average', 'rcmax' or 'BMA' for combining semantic similarity scores of multiple GO terms associated with protein.

Details

This function calculates protein/DNA sequence similarity based on Gene Ontology (GO) similarity.

Value

A n x n similarity matrix.

Author(s)

Min-feng Zhu <[e-mail]>, Nan Xiao <http://nanx.me>

See Also

See twoGOSim for calculating the GO semantic similarity between two groups of GO terms or two Entrez gene IDs. See parSeqSim for paralleled protein/DNA similarity calculation based on Smith-Waterman local alignment.

Examples

# Be careful when testing this since it involves GO similarity computation
# and might produce unpredictable results in some environments

require(GOSemSim)
require(org.Hs.eg.db)

# by GO Terms
go1 = c('GO:0005215', 'GO:0005488', 'GO:0005515', 'GO:0005625', 'GO:0005802', 'GO:0005905')  # AP4B1
go2 = c('GO:0005515', 'GO:0005634', 'GO:0005681', 'GO:0008380', 'GO:0031202')  # BCAS2
go3 = c('GO:0003735', 'GO:0005622', 'GO:0005840', 'GO:0006412')  # PDE4DIP
glist = list(go1, go2, go3)
gsimmat1 = parGOSim(glist, type = 'go', ont = 'CC')
print(gsimmat1)

# by Entrez gene id
genelist = list(c('150', '151', '152', '1814', '1815', '1816'))
gsimmat2 = parGOSim(genelist, type = 'gene')
print(gsimmat2)

BioMedR documentation built on Nov. 17, 2017, 10:08 a.m.