getTopDiseaseLncRNAs: Get the Disease Risk LncRNAs
In LncPriCNet: Prioritizing Candidate LncRNAs Based on a Composite Multi-Level Network

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

View source: R/getTopDiseaseLncRNAs.R

prioritize the disease candidate lncRNAs by integrated multi-omics information.

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    getTopDiseaseLncRNAs(pheSeed = NULL, genSeed = NULL, lncSeed = NULL, 
			candidates = NULL, showTop = 30, gamma = 0.7, x = 1/3, y = 1/3, 
			a = 1/3, b = 1/3, GNet, PNet, LNet, GLNet, PGNet, PLNet)

`pheSeed`	A character vector, represents the disease users want to study. Users should input diseaseName.
`genSeed`	A character vector, The gene seeds are the known disease genes of corresponding phenotype. Users should input a gene seed vector.
`lncSeed`	A character vector, The lncRNA seeds are the known disease lncRNAs of corresponding phenotype. Users should input a lncRNA seed vector.
`candidates`	A character vector. Users should input lncRNA candidates, a lncRNA seed vector.
`showTop`	An integer. The number of top ranked candidate lncRNAs users want to show.
`gamma`	Restart probability in RWR method. A value ranges from 0 to 1. The default value is 0.7.
`x`	Jumping probability between gene network and phenotype network. A value ranges from 0 to 1. The default value is 1/3.
`y`	Jumping probability between gene network and lncRNA network. A value ranges from 0 to 1. The default value is 1/3.
`a`	a denote the importance of the gene network. A value ranges from 0 to 1. The default value is 1/3.
`b`	b denote the importance of the phenotype network. A value ranges from 0 to 1. The default value is 1/3.
`GNet`	An adjacency matrix of the gene network with colnames and rownames representing genes. The value in it ranges from 0 to 1.
`PNet`	An adjacency matrix of the phenotype network with colnames and rownames representing phenotypes. The value in it ranges from 0 to 1.
`LNet`	An adjacency matrix of the lncRNA network with colnames and rownames representing lncRNAs. The value in it ranges from 0 to 1.
`GLNet`	An adjacency matrix of the gene-lncRNA network with colnames representing lncRNAs and rownames representing genes. The value in it ranges from 0 to 1.
`PGNet`	An adjacency matrix of the phenotype-gene network with colnames representing genes and rownames representing phenotypes. The value in it ranges from 0 to 1.
`PLNet`	An adjacency matrix of the phenotype-lncRNA network with colnames representing lncRNAs and rownames representing phenotypes. The value in it ranges from 0 to 1.

The function getTopDiseaseLncRNAs could get the top ranked candidate lncRNAs by prioritization of the disease candidate lncRNAs using known disease seed nodes to perform random walk on multi-omics network. Note: If users want to use seeds we provided, pheSeed, genSeed and lncSeed can be obtained by getDiseaseInf.

A dataframe.

Qianlan Yao <yaoqianlan@yahoo.com>

DiseaseInfList, getCoExpGeneofLncs, getDiseaseInf.

## Not run: 
#############    Prioritize candidate lncRNAs   ################ 

## Here we use six fake matrix(networks).  
data("GNetExample")
data("GLNetExample")
data("PNetExample")
data("LNetExample")
data("PGNetExample")
data("PLNetExample")

## Get three types seeds from DiseaseInfList we provided. 
diseaseName<-"BREAST CANCER" ;
data("DiseaseInfList")
loci<-match(diseaseName,DiseaseInfList[["OMIMName"]]);
pheSeedExample<-DiseaseInfList[loci,"OMIMId"];
genSeedExample<-unlist(strsplit(as.character(DiseaseInfList[loci,"DGenes"]),";"));
lncSeedExample<-unlist(strsplit(as.character(DiseaseInfList[loci,"DLncs"]),";"));
PNodes<-colnames(PNetExample) ;
GNodes<-colnames(GNetExample);
LNodes<-colnames(LNetExample);
pheSeedResult<-pheSeedExample;
genSeedResult<-genSeedExample;
lncSeedResult<-lncSeedExample;

## Get candidates.
candidateResult<-setdiff(LNodes,lncSeedResult);
##Run getTopDiseaseLncRNAs
example<-getTopDiseaseLncRNAs(pheSeed=pheSeedResult,genSeed=genSeedResult,lncSeed=lncSeedResult,
       candidates=candidateResult,showTop=30,GNet=GNetExample,PNet=PNetExample,LNet=LNetExample,
	   GLNet=GLNetExample,PGNet=PGNetExample,PLNet=PLNetExample);
head(example)



## End(Not run)

      [,1]                                                                                                                                   
 [1,] "The number of the phenotype seeds you input are:  1"                                                                                  
 [2,] "The number of the phenotype seeds used in prioritizing the candidate lncRNA are:  1"                                                  
 [3,] "The phenotype seeds used in prioritizing the candidate lncRNA are:  114480"                                                           
 [4,] "The number of the lncRNA seeds you input are:  11"                                                                                    
 [5,] "The number of the lncRNA seeds used in prioritizing the candidate lncRNA are:  11"                                                    
 [6,] "The lncRNA seeds used in prioritizing the candidate lncRNA are:  BCYRN1;CDKN2B-AS1;GAS5;H19;HOTAIR;MIR31HG;MALAT1;MEG3;PVT1;UCA1;XIST"
 [7,] "The number of the gene seeds you input are:  11"                                                                                      
 [8,] "The number of the gene seeds used in prioritizing the candidate lncRNA are:  11"                                                      
 [9,] "The gene seeds used in prioritizing the candidate lncRNA are:  BRCA2;PALB2;NBN;PIK3CA;RAD51;AKT1;CHEK2;XRCC3;BRCA1;BRIP1;FAM175A"     
[10,] "The number of the candidate lncRNA you input are:  499"                                                                               
[11,] "The number of lncRNA candidates to be prioritized are  499"                                                                           
[1] 30
              Rank  topLncRNAsID topLncRNAsScore
C6orf3           1        C6orf3    0.0002979457
RP11-228B15.4    2 RP11-228B15.4    0.0002968836
CACNA1G-AS1      3   CACNA1G-AS1    0.0002881332
TDRG1            4         TDRG1    0.0002796020
RP11-844P9.2     5  RP11-844P9.2    0.0002771580
HCG11            6         HCG11    0.0002662392