FunSim: calculate disease similarity by FunSim
In dSimer: Integration of Disease Similarity Methods

Description Usage Arguments Value Author(s) References See Also Examples

given two vectors of diseases, a list of disease-gene associations , and a list of gene-gene log-likelihood score from HumanNet, this function will calculate disease similarity by method FunSim

1	FunSim(D1, D2, d2g, LLSnList)

`D1`	a vector consists disease ids
`D2`	another vector consists disease ids
`d2g`	a list of disease-gene associations, while gene ids should be entrez id.
`LLSnList`	a list of gene-gene log-likelihood score from HumanNet

a matrix of disease disease simialrity which rownames is D1 and colnames is D2

Peng Ni, Min Li

Cheng L, Li J, Ju P, et al. SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association[J]. PloS one, 2014, 9(6): e99415.

LLSn2List

## in this method, we must use disease-gene associations 
## which genes are represented by entrez ids because of
## HumanNet
data(d2g_fundo_entrezid)
data(HumanNet_sample)
## we specified 5 DOIDs to match Human_sample
ds<-c("DOID:8176","DOID:2394","DOID:3744","DOID:8466","DOID:5679")
llsnlist<-LLSn2List(HumanNet_sample)
FunSim(ds,ds,d2g_fundo_entrezid,llsnlist)

Loading required package: igraph

Attaching package: 'igraph'

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union



calculating simialrity matrix of diseases.. this may take a lot of time..
done..
             DOID:8176  DOID:2394    DOID:3744    DOID:8466 DOID:5679
DOID:8176 1.0000000000 0.43350044 0.4476822789 0.0002666029 0.1457867
DOID:2394 0.4335004444 1.00000000 0.4222353572 0.0166884115 0.1592188
DOID:3744 0.4476822789 0.42223536 1.0000000000 0.0001286379 0.1293250
DOID:8466 0.0002666029 0.01668841 0.0001286379 1.0000000000 0.1349979
DOID:5679 0.1457866621 0.15921884 0.1293250308 0.1349979009 1.0000000