package GraphAlgorithm;
import java.io.BufferedWriter;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import network.CommGeneticsLoader;
import network.CommLoader;
import network.DisGraph;
import network.SparseVector;
import util.DCNOMIMUMLSIDmap;
public class DeNovoPred {
private Map<String, Integer> generank = new HashMap<>();
/**
* Initializes a new DovovoPrediction object
* @param cgg a CommGeneticsGraph
* @param dis the disease whose genes will be de novo predicted
* @throws IOException if dis doesn't exist
*/
public DeNovoPred(DisGraph cgg, String dis, double p) throws IOException{
// check if the disease is in disease comorbidity network
String dis_id = null;
if (DCNOMIMUMLSIDmap.dcnnameidmap.containsKey(dis)) {
dis_id = DCNOMIMUMLSIDmap.dcnnameidmap.get(dis);
} else {
System.out.println("No such disease in this network!");
}
// Critical part for removing all disease gene edges
int dis_idx = CommGeneticsLoader.entry_index.get(dis_id); // for CommGeneticsloader from netfile
// int dis_idx = CommLoader.disease_index.get(dis_id); // for CommGeneticsloader from net
System.out.printf("Disease: %s\n", dis);
System.out.printf("Disease index: %s\n", dis_idx);
System.out.printf("Disease id: %s\n", dis_id);
System.out.println("Disease_gene edges before removing: " + cgg.getNet().getNeibor(dis_idx));
cgg.removeEdges(dis_idx); // key code for do novo prediction
System.out.println("Disease_gene edges after removing: " + cgg.getNet().getNeibor(dis_idx));
// Random walk to rank disease genes
List<String> dislist = new ArrayList<>();
dislist.add(dis_id);
SparseVector seed = RandomWalk.createSeedVector(dislist);
RandomWalk rm = new RandomWalk(cgg, seed, p);
generank = rm.getRWRank();
}
/**
* Get de novo prediction gene ranks for specific disease
* @return de novo prediction gene ranks for specific disease
*/
public Map<String, Integer> getDoNovo() {
return generank;
}
/**
* Write gene-rank pairs into a CSV file, format is "Gene,Rank,Percentage"
* @param dn de novo prediction map
* @param dnfile a file to be written
* @throws IOException
*/
public void saveDoNovo(Map<String, Integer> dn, String dnfile) throws IOException {
BufferedWriter bw = new BufferedWriter(new FileWriter(new File(dnfile)));
bw.write("Gene" + "," + "Rank" + "," + "Percentage" + "\n");
for (String gene : dn.keySet()) {
// System.out.println(sortedgenemap.get(s));
int rank = dn.get(gene);
double perc = rank * 1.0 / CommGeneticsLoader.num_gene * 100;
bw.write(gene + "," + rank + "," + perc + "\n");
}
bw.close();
}
public static void main(String[] args) throws IOException {
// step 1: build DCN-PPI network
System.out.println("Building DCN network...");
// String commnetfile = args[0];
// String ppifile = args[1];
// String disgenefile = args[2];
String commnetfile = "./data/fares_comm_net_lift_final_abbr.txt";
String ppifile = "./data/gene_gene_string_cut.txt";
String disgenefile = "./data/OMIM_disease_gene_umls_id_diso";
// String dcnmapfile = args[3];
// String omimmapfile = args[4];
String dcnmapfile = "./data/term_umls_id_diso";
String omimmapfile = "./data/OMIM_umls_id_diso";
util.DCNOMIMUMLSIDmap.createDCNIdNameMap(dcnmapfile);
util.DCNOMIMUMLSIDmap.createOMIMIdNameMap(omimmapfile);
String DCN_dis = "dementia";
String OMIM_pat = "alzheimer";
DCNOMIMUMLSIDmap domim = new DCNOMIMUMLSIDmap(DCN_dis, OMIM_pat);
Map<String, List<String>> dcn_omim = domim.getDCNOMIMUMLSIDmap();
DisGraph cgg = null;
try {
cgg = CommGeneticsLoader.createCommGeneticsGraph(commnetfile, ppifile, disgenefile, dcn_omim);
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
System.out.println("Done!");
// step 2: optimize restart probability
// String rulefile = args[5];
// String donovoDir = args[6]
// String predType = args[7]
String rulefile = "./data/ID_indications_all_clean_width_umls_id_diso_filtered_sp_lift_1_0.000002_3_processed.txt";
String donovoDir = "./results/evaluation/";
String predType = "pred" //"optimize", "random" or "pred"
if (preType=="optimize") {
/**
* do novo prediction for different restart probabilities
*/
System.out.println("Starting do novo gene prediction for " + DCN_dis + "!");
List<Double> ps = new ArrayList<Double>();
for(int i=1; i<10; i++){
ps.add(i * 0.1);
}
int count = 1;
for(double p : ps){
System.out.println("\nTesting " + count + " of " + ps.size());
DeNovoPred dnp = new DeNovoPred(cgg, DCN_dis, p);
Map<String, Integer> generank = dnp.getDoNovo();
String donovofile = donovoDir + "commnet_opti_" + P + DCN_dis + ".csv";
dnp.saveDoNovo(generank, donovofile);
count++;
}
}
// step 3: get gene ranks for randomized network
if (preType=="random") {
// #########################################################################
// ----------------------- Method: Erdos-Renyi graph ---------------------------------
// #########################################################################
System.out.println("\nStaring random node do novo prediction......\n");
// /*
// * Build the bipartite network
CommLoader.readAssocRules(rulefile);
DisGraph commnet = CommLoader.createCommNet(rulefile);
int V = commnet.getNodes();
double p = (double) V / (V*(V-1)/2);
System.out.println("Probability: " + p);
CommLoader.readPPI(ppifile);
DisGraph ppinet = CommLoader.createPPINet(ppifile);
List<String> entry_list = new ArrayList<String>();
List<String> disease_list = new ArrayList<String>();
disease_list = util.CollectionsEx.setToList(CommLoader.disease_set);
entry_list.addAll(disease_list);
entry_list.addAll(CommLoader.gene_list);
CommGeneticsLoader.createIndex(entry_list);
CommGeneticsLoader.num_disease = disease_list.size();
CommGeneticsLoader.entry_list = entry_list;
CommGeneticsLoader.num_gene = CommLoader.gene_list.size();
Map<Integer, List<Integer>> dis_gene = CommLoader.readDisGene(disgenefile, dcn_omim);
int N = 1000;
double P = 0.5;
for (int i=0; i<N; i++) {
System.out.println();
if (i > 10 && i % 100 == 0) {
System.out.printf("Finish %d of %d prediction!", i, N);
}
DisGraph randnet = GraphGenerator.simple(V, p);
System.out.println("Total nodes in randamized disease graph: " + randnet.getNodes());
System.out.println("Total edges in randomized disease graph: " + randnet.getEdges());
DisGraph cgg = CommGeneticsLoader.createCommGeneticsGraph(randnet, ppinet, dis_gene);
System.out.println("Total nodes in randamized heterogeneous graph: " + cgg.getNodes());
System.out.println("Total edges in randomized heterogeneous graph: " + cgg.getEdges());
DeNovoPred dnp = new DeNovoPred(cgg, DCN_dis, P); //!speed limit operation
Map<String, Integer> generank = dnp.getDoNovo();
System.out.println("Size of gene rank:" + generank.size());
String donovofile = donovoDir + "random_er_" + P + "_" + i + "_" + DCN_dis + ".csv";
dnp.saveDoNovo(generank, donovofile);
}
}
//Step 4: get gene rank from DCN
if (preType=="pred") {
DeNovoPred dnp = new DeNovoPred(cgg, DCN_dis, 0.5);
Map<String, Integer> generank = dnp.getDoNovo();
System.out.println("Size of gene rank:" + generank.size());
String donovofile = donovoDir + "commnet_" + 0.5 + "_" + DCN_dis + ".csv";
dnp.saveDoNovo(generank, donovofile);
}
}
}
Datasets
Models
