Fixed bug: previously reset likelihoods after each region/exon.
Better comments/documentation added git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1386 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
sjia
parent
0d47798721
commit
d60d5aa516
|
|
@ -8,6 +8,7 @@ package org.broadinstitute.sting.playground.gatk.walkers.HLAcaller;
|
|||
import org.broadinstitute.sting.gatk.contexts.AlignmentContext;
|
||||
import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
|
||||
import org.broadinstitute.sting.gatk.refdata.RefMetaDataTracker;
|
||||
import org.broadinstitute.sting.utils.BaseUtils;
|
||||
import org.broadinstitute.sting.utils.cmdLine.Argument;
|
||||
import org.broadinstitute.sting.utils.Pair;
|
||||
import org.broadinstitute.sting.utils.ReadBackedPileup;
|
||||
|
|
@ -37,141 +38,134 @@ public class CallHLAWalker extends LocusWalker<Integer, Pair<Long, Long>>{
|
|||
int[] HLAstoppos;
|
||||
int numHLAlleles = 0;
|
||||
double[][] Prob; String[][] Alleles;
|
||||
int j1, k1, j2, k2;
|
||||
|
||||
Hashtable Scores = new Hashtable();
|
||||
|
||||
//HLAreads.add("Italian Riviera");
|
||||
boolean DatabaseLoaded = false;
|
||||
boolean PrintedOutput = false;
|
||||
|
||||
public Pair<Long, Long> reduceInit() {
|
||||
try{
|
||||
out.printf("Reading HLA database ...");
|
||||
FileInputStream fstream = new FileInputStream(HLAdatabaseFile);
|
||||
// Get the object of DataInputStream
|
||||
DataInputStream in = new DataInputStream(fstream);
|
||||
BufferedReader br = new BufferedReader(new InputStreamReader(in));
|
||||
String strLine; String [] s = null;
|
||||
//Read File Line By Line
|
||||
while ((strLine = br.readLine()) != null) {
|
||||
s = strLine.split("\\t");
|
||||
if (s.length>=10){
|
||||
HLAreads.add(CigarFormatted(s[5],s[9]));
|
||||
HLAcigars.add(s[5]);
|
||||
HLAnames.add(s[0]);
|
||||
HLApositions.add(s[3]);
|
||||
//System.out.println (s[0] + "\t" + s[3]);
|
||||
//Load sequences corresponding to HLA alleles from sam file
|
||||
if (!DatabaseLoaded){
|
||||
try{
|
||||
out.printf("Reading HLA database ...");
|
||||
FileInputStream fstream = new FileInputStream(HLAdatabaseFile);
|
||||
DataInputStream in = new DataInputStream(fstream);
|
||||
BufferedReader br = new BufferedReader(new InputStreamReader(in));
|
||||
String strLine; String [] s = null;
|
||||
//Read File Line By Line
|
||||
while ((strLine = br.readLine()) != null) {
|
||||
s = strLine.split("\\t");
|
||||
if (s.length>=10){
|
||||
//Parse the reads with cigar parser
|
||||
HLAreads.add(CigarFormatted(s[5],s[9]));
|
||||
HLAcigars.add(s[5]);
|
||||
HLAnames.add(s[0]);
|
||||
HLApositions.add(s[3]);
|
||||
}
|
||||
}
|
||||
}
|
||||
in.close();
|
||||
int n = HLApositions.size();
|
||||
numHLAlleles = n;
|
||||
HLAstartpos = new int[n]; HLAstoppos = new int[n];
|
||||
Prob = new double[n][n];
|
||||
for (int i = 0; i < n; i++){
|
||||
HLAstartpos[i]=Integer.parseInt(HLApositions.get(i));
|
||||
HLAstoppos[i]=HLAstartpos[i]+HLAreads.get(i).length()-1;
|
||||
for (int j = 0; j <n; j++){
|
||||
Prob[i][j]=0;
|
||||
}
|
||||
//System.out.println (HLAstartpos[i] + " to " + HLAstoppos[i]);
|
||||
}
|
||||
out.printf("DONE!\n");
|
||||
}catch (Exception e){//Catch exception if any
|
||||
System.err.println("Error: " + e.getMessage());
|
||||
}
|
||||
in.close();
|
||||
int n = HLApositions.size(); numHLAlleles = n;
|
||||
HLAstartpos = new int[n]; HLAstoppos = new int[n];
|
||||
Prob = new double[n][n];
|
||||
|
||||
//out.printf("%s,%s\n",HLAnames.get(22),HLAnames.get(68));
|
||||
//String read = HLAreads.get(22);
|
||||
//String cigar = HLAcigars.get(22);
|
||||
//out.printf("%s,%s\n",cigar,read);
|
||||
//HLAreads.set(22, CigarFormatted(cigar,read));
|
||||
//HLAreads.set(68, CigarFormatted(HLAcigars.get(68),HLAreads.get(68)));
|
||||
out.printf("Comparing reads to database ...\n");
|
||||
int j1 = 80, k1 = 96, j2 = 80, k2 = 114;
|
||||
out.printf("%s,%s\t%s,%s\n",HLAnames.get(j1),HLAnames.get(k1),HLAnames.get(j2),HLAnames.get(k2));
|
||||
for (int i = 0; i < n; i++){
|
||||
//Find start and stop positions for each allele
|
||||
HLAstartpos[i]=Integer.parseInt(HLApositions.get(i));
|
||||
HLAstoppos[i]=HLAstartpos[i]+HLAreads.get(i).length()-1;
|
||||
//Initialize matrix of probabilities / likelihoods
|
||||
for (int j = 0; j <n; j++){
|
||||
Prob[i][j]=0;
|
||||
}
|
||||
//For debugging: get index for specific alleles
|
||||
if (HLAnames.get(i).equals("HLA_A*310102"))
|
||||
j1 = i;
|
||||
if (HLAnames.get(i).equals("HLA_A*320101"))
|
||||
k1 = i;
|
||||
if (HLAnames.get(i).equals("HLA_A*330301"))
|
||||
j2 = i;
|
||||
if (HLAnames.get(i).equals("HLA_A*0265"))
|
||||
k2 = i;
|
||||
}
|
||||
out.printf("DONE!\n");
|
||||
}catch (Exception e){//Catch exception if any
|
||||
System.err.println("Error: " + e.getMessage());
|
||||
}
|
||||
|
||||
DatabaseLoaded = true;
|
||||
out.printf("Comparing reads to database ...\n");
|
||||
|
||||
//For debugging: prints which HLA alleles were indexed before
|
||||
//out.printf("%s,%s\t%s,%s\n",HLAnames.get(j1),HLAnames.get(k1),HLAnames.get(j2),HLAnames.get(k2));
|
||||
}
|
||||
return new Pair<Long,Long>(0l,0l);
|
||||
}
|
||||
|
||||
private String CigarFormatted(String cigar, String read){
|
||||
String formattedRead = "";
|
||||
char c;
|
||||
String count;
|
||||
// returns a cigar-formatted sequence (removes insertions, inserts 'D' to where deletions occur
|
||||
String formattedRead = ""; char c; String count;
|
||||
int cigarPlaceholder = 0; int subcigarLength = 0;
|
||||
int readPlaceholder = 0; int subreadLength = 0;
|
||||
//out.printf("%s\n",cigar);
|
||||
|
||||
//reads cigar string
|
||||
for (int i = 0; i < cigar.length(); i++){
|
||||
c = cigar.charAt(i);
|
||||
if (c == 'M'){
|
||||
//If reach M for match/mismatch, get number immediately preceeding 'M' and tack on that many characters to sequence
|
||||
subcigarLength = i-cigarPlaceholder;
|
||||
count = cigar.substring(cigarPlaceholder, i);
|
||||
|
||||
//read.substring(readPlaceholder, subreadLength)
|
||||
|
||||
subreadLength = Integer.parseInt(count);
|
||||
formattedRead = formattedRead + read.substring(readPlaceholder, readPlaceholder+subreadLength);
|
||||
|
||||
//out.printf("%sM,%s,%s\n", count,readPlaceholder,readPlaceholder+subreadLength);
|
||||
//increment placeholders
|
||||
cigarPlaceholder = i+1;
|
||||
readPlaceholder = readPlaceholder + subreadLength;
|
||||
|
||||
readPlaceholder = readPlaceholder + subreadLength;
|
||||
} else if (c == 'I'){
|
||||
//***NOTE: To be modified later if needed (insertions removed here)***
|
||||
|
||||
//If reaches I for insertion, get number before 'I' and skip that many characters in sequence
|
||||
count = cigar.substring(cigarPlaceholder, i);
|
||||
subreadLength = Integer.parseInt(count);
|
||||
//formattedRead = formattedRead + read.substring(readPlaceholder, subreadLength);
|
||||
//out.printf("%sI,%s,%s\n", count,readPlaceholder,readPlaceholder+subreadLength);
|
||||
|
||||
//increment placeholders without adding inserted bases to sequence (effectively removes insertion).
|
||||
cigarPlaceholder = i+1;
|
||||
readPlaceholder = readPlaceholder + subreadLength;
|
||||
|
||||
readPlaceholder = readPlaceholder + subreadLength;
|
||||
} else if (c == 'D'){
|
||||
//If reaches D for deletion, insert 'D' into sequence as placeholder
|
||||
count = cigar.substring(cigarPlaceholder, i);
|
||||
subreadLength = Integer.parseInt(count);
|
||||
|
||||
//Add one 'D' for each deleted base
|
||||
String deletion = "";
|
||||
for (int j = 1; j <= subreadLength; j++){
|
||||
deletion = deletion + "D";
|
||||
}
|
||||
//out.printf("%sD,%s,%s\n", count,readPlaceholder,readPlaceholder+subreadLength);
|
||||
|
||||
//update placeholders
|
||||
formattedRead = formattedRead + deletion;
|
||||
cigarPlaceholder = i+1;
|
||||
//readPlaceholder = readPlaceholder + subreadLength;
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
//out.printf("%s\n",formattedRead);
|
||||
|
||||
return formattedRead;
|
||||
}
|
||||
|
||||
private static int unsignedByteToInt(byte b) {
|
||||
//converts base quality from byte to int (not really needed)
|
||||
return (int) b & 0xFF;
|
||||
}
|
||||
|
||||
public Integer map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context) {
|
||||
|
||||
//Create new context with mapping quality >= 20
|
||||
List<SAMRecord> reads = context.getReads();
|
||||
List<Integer> offsets = context.getOffsets();
|
||||
GenomeLoc Gloc = context.getLocation();
|
||||
//List<SAMRecord> newreads = Arrays.asList();
|
||||
//List<Integer> newoffsets = Arrays.asList();
|
||||
|
||||
//remove reads with mapping quality < 20
|
||||
|
||||
//for (int i = 0; i < reads.size(); i++){
|
||||
//out.printf("i=%s,s=%s",i,reads.size());
|
||||
//SAMRecord r = reads.get(i);
|
||||
//if (r.getMappingQuality() < 20){
|
||||
//out.printf(",%s removed",i);
|
||||
//reads.remove(i);
|
||||
//offsets.remove(i);
|
||||
//i--;
|
||||
//}
|
||||
//out.printf("\n");
|
||||
//}
|
||||
|
||||
//reset context to include only high quality reads
|
||||
context = new AlignmentContext(Gloc,reads,offsets);
|
||||
|
||||
//Create pileup of reads at this locus using filtered context
|
||||
//Create pileup of reads at this locus
|
||||
ReadBackedPileup pileup = new ReadBackedPileup(ref.getBase(), context);
|
||||
|
||||
String bases = pileup.getBases();
|
||||
|
||||
long loc = context.getPosition();
|
||||
|
||||
if( context.getReads().size() > 0 ) {
|
||||
|
|
@ -183,104 +177,105 @@ public class CallHLAWalker extends LocusWalker<Integer, Pair<Long, Long>>{
|
|||
String c1 = ""; String c2 = "";
|
||||
long pos_k = 0; long pos_j = 0;
|
||||
|
||||
for (int i = 0;i < context.getReads().size();i++){
|
||||
//out.printf("%s%s ",i,bases.charAt(i));
|
||||
char base = bases.charAt(i);
|
||||
if (base == 'A'){numAs++;}
|
||||
if (base == 'C'){numCs++;}
|
||||
if (base == 'T'){numTs++;}
|
||||
if (base == 'G'){numGs++;}
|
||||
|
||||
}
|
||||
//Debugging purposes: print location, reference base, pileup, and count (before quality filtering)
|
||||
//out.printf("%s\t", context.getLocation());
|
||||
//out.printf("ref=%s\t", ref);
|
||||
//out.printf("%sAs\t%sCs\t%sTs\t%sGs\t",numAs,numCs,numTs,numGs);
|
||||
int j1 = 80, k1 = 96, j2 = 80, k2 = 114;
|
||||
//out.printf("ref=%s\t", ref.getBase());
|
||||
//out.printf("%s\t",pileup.getBases().toString());
|
||||
//out.printf("%s\t",pileup.getBasePileupAsCountsString());
|
||||
|
||||
|
||||
//Calculate posterior probabilities!
|
||||
// todo -- note this now uses a flat prior -- rather than a reference biased prior
|
||||
NewHotnessGenotypeLikelihoods G = new NewHotnessGenotypeLikelihoods();
|
||||
|
||||
// todo -- note I've removed the Q20 restriction -- the genotyper takes care of this automatically
|
||||
G.add(pileup);
|
||||
//I've tried simply adding the entire pileup to G, but quality scores are not checked, and 'N' bases throw an error
|
||||
//(NewHotnessGenotypeLikelihoods potentially has bug on line 57)
|
||||
//G.add(pileup);
|
||||
|
||||
//Store confidence scores
|
||||
// Todo -- there's no need for the hash table now -- you can just use getLikeliood and the DiploidGenotype interface
|
||||
//Check for bad bases and ensure mapping quality myself. This works.
|
||||
for (int i = 0; i < context.getReads().size(); i++) {
|
||||
SAMRecord read = context.getReads().get(i);
|
||||
int offset = context.getOffsets().get(i);
|
||||
char base = read.getReadString().charAt(offset);
|
||||
byte qual = read.getBaseQualities()[offset];
|
||||
int mapquality = read.getMappingQuality();
|
||||
if (mapquality >= 20 && BaseUtils.simpleBaseToBaseIndex(base) != -1) {
|
||||
if (base == 'A'){numAs++;}
|
||||
if (base == 'C'){numCs++;}
|
||||
if (base == 'T'){numTs++;}
|
||||
if (base == 'G'){numGs++;}
|
||||
//consider base in likelihood calculations if it looks good and has high mapping score
|
||||
G.add(base, qual);
|
||||
}
|
||||
}
|
||||
|
||||
//Debugging purposes
|
||||
//out.printf("A[%s]\tC[%s]\tT[%s]\tG[%s]\t",numAs,numCs,numTs,numGs);
|
||||
|
||||
|
||||
//Store confidence scores - this is a local hash that we use to get likelihood given a particular genotype
|
||||
Scores = new Hashtable();
|
||||
for ( DiploidGenotype g : DiploidGenotype.values() ) {
|
||||
Scores.put(g.toString(), G.getLikelihood(g));
|
||||
}
|
||||
|
||||
//Update probabilities for combinations of alleles
|
||||
//For each HLA allele
|
||||
//Get likelihood score for homozygous ref: used to normalize likelihoood scores at 0.
|
||||
String homref = String.valueOf(ref.getBase())+String.valueOf(ref.getBase());
|
||||
Double homreflikelihood = Double.parseDouble((String) Scores.get(homref).toString());
|
||||
|
||||
|
||||
//Update likelihood for each combinations of alleles
|
||||
Double likelihood = 0.0;
|
||||
String r1 = "", r2 = "", s1 = "", s2 = "";
|
||||
j1 = 80; k1 = 96; j2 = 80; k2 = 114;
|
||||
for (int j = 0; j < numHLAlleles; j++){
|
||||
//out.print(j+","+loc + "," + HLAstartpos[j] + "," + HLAstoppos[j]);
|
||||
//check if allele overlaps current position
|
||||
|
||||
//check if allele 1 overlaps current position
|
||||
if (loc >= HLAstartpos[j] && loc <= HLAstoppos[j]){
|
||||
pos_j = loc - HLAstartpos[j];
|
||||
c1 = Character.toString(Character.toUpperCase(HLAreads.get(j).charAt((int) pos_j)));
|
||||
|
||||
if (j == j1){ //C*010201
|
||||
r1 = c1;
|
||||
}
|
||||
if (j == k1){ //C*070101
|
||||
r2 = c1;
|
||||
}
|
||||
if(j == j2){ //C*010201
|
||||
s1 = c1;
|
||||
}
|
||||
if (j == k2){ //C*150201
|
||||
s2 = c1;
|
||||
}
|
||||
//Extract bases for HLA alleles indicated in reduceInit (for debugging)
|
||||
if (j == j1) r1 = c1;
|
||||
if (j == k1) r2 = c1;
|
||||
if (j == j2) s1 = c1;
|
||||
if (j == k2) s2 = c1;
|
||||
|
||||
//Updade likelihoods
|
||||
for (int k = 0; k < numHLAlleles; k++){
|
||||
//out.print(k+","+loc + "," + HLAstartpos[j] + "," + HLAstoppos[j]);
|
||||
|
||||
//check if allele 2 overlaps current position
|
||||
if (loc >= HLAstartpos[k] && loc <= HLAstoppos[k]){
|
||||
pos_k = loc - HLAstartpos[k];
|
||||
c2 = Character.toString(Character.toUpperCase(HLAreads.get(k).charAt((int) pos_k)));
|
||||
//out.printf("j=%s,k=%s,C1=%s,C2=%s,",j,k,c1,c2);
|
||||
|
||||
//updates likelihoods for both permutations of the alleles, normalized to the likelihood for homozygous reference
|
||||
|
||||
if (Scores.containsKey(c1 + c2)){
|
||||
String base=c1 + c2;
|
||||
Prob[j][k]= Prob[j][k]+Double.parseDouble((String) Scores.get(base));
|
||||
//out.printf("P(%s)=%s\t",base,Prob[j][k]);
|
||||
|
||||
likelihood = Double.parseDouble((String) Scores.get(c1 + c2).toString());
|
||||
Prob[j][k]= Prob[j][k]+ likelihood - homreflikelihood;
|
||||
|
||||
}else if(Scores.containsKey(c2 + c1)){
|
||||
String base=c2 + c1;
|
||||
Prob[j][k]= Prob[j][k]+Double.parseDouble((String) Scores.get(base));
|
||||
//out.printf("P(%s)=%s\t",base,Prob[j][k]);
|
||||
|
||||
likelihood = Double.parseDouble((String) Scores.get(c2 + c1).toString());
|
||||
Prob[j][k]= Prob[j][k]+ likelihood - homreflikelihood;
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
//out.printf("%s%s:%5.0f\t%s%s:%5.0f\t",r1,r2,Prob[j1][k1],s1,s2,Prob[j2][k2]);
|
||||
//out.printf("%s %5.0f\t",base,score);
|
||||
|
||||
if ( !suppressPrinting ){
|
||||
}
|
||||
|
||||
//out.printf("\t");
|
||||
//mGenotypes.get(0).getConfidenceScore().
|
||||
//out.printf("RG for first read: %s%n",context.getReads().get(0).getReadName());
|
||||
//Debugging: print updated likelihoods for 2 sets of HLA alleles, as well as normalized likelihoods for all 10 genotypes
|
||||
//out.printf("%s%s:%5.0f\t%s%s:%5.0f\t",r1,r2,Prob[j1][k1],s1,s2,Prob[j2][k2]);
|
||||
for ( DiploidGenotype g : DiploidGenotype.values() ) {
|
||||
//out.printf("%s %5.0f\t",g.toString(),likelihood - homreflikelihood);
|
||||
}
|
||||
//out.printf("\n");
|
||||
}
|
||||
}
|
||||
|
||||
return context.getReads().size();
|
||||
|
||||
}
|
||||
|
||||
private double[] priorsArray(String priorsString) {
|
||||
String[] pstrs = priorsString.split(",");
|
||||
double[] pdbls = new double[pstrs.length];
|
||||
|
||||
for (int i = 0; i < pstrs.length; i++) {
|
||||
pdbls[i] = Double.valueOf(pstrs[i]);
|
||||
}
|
||||
|
||||
return pdbls;
|
||||
}
|
||||
|
||||
public boolean isReduceByInterval() {
|
||||
|
|
@ -294,27 +289,55 @@ public class CallHLAWalker extends LocusWalker<Integer, Pair<Long, Long>>{
|
|||
}
|
||||
|
||||
public void onTraversalDone(Pair<Long, Long> result) {
|
||||
double max = 0; int max_i =0; int max_j = 0;
|
||||
double max_2 = 0; int max_i_2 =0; int max_j_2 = 0;
|
||||
double max_3 = 0; int max_i_3 =0; int max_j_3 = 0;
|
||||
|
||||
out.printf("\n");
|
||||
for (int i = 0; i < numHLAlleles; i++){
|
||||
for (int j = 0; j < numHLAlleles; j++){
|
||||
if (i >= j ){
|
||||
out.printf("%s\t%s\t%5.0f\n",HLAnames.get(i),HLAnames.get(j),Prob[i][j]);
|
||||
}
|
||||
if (Prob[i][j] > max){
|
||||
max_3 = max_2; max_i_3 = max_i_2; max_j_3 = max_j_2;
|
||||
max_2 = max; max_i_2 = max_i; max_j_2 = max_j;
|
||||
max = Prob[i][j]; max_i = i; max_j = j;
|
||||
//Print HLA allele combinations with highest likelihood sums
|
||||
if (!PrintedOutput){
|
||||
double max = 0; int i_max =0; int j_max = 0;
|
||||
double m2 = 0; int i_max_2 =0; int j_max_2 = 0;
|
||||
double m3 = 0; int i_max_3 =0; int j_max_3 = 0;
|
||||
|
||||
out.printf("\n");
|
||||
|
||||
//Find max scores.
|
||||
for (int i = 0; i < numHLAlleles; i++){
|
||||
for (int j = 0; j < numHLAlleles; j++){
|
||||
if (i >= j){
|
||||
//Print likelihoods for all alleles
|
||||
out.printf("%s\t%s\t%5.0f",HLAnames.get(i),HLAnames.get(j),Prob[i][j]);
|
||||
if (Prob[i][j] > max){
|
||||
m3 = m2; i_max_3 = i_max_2; j_max_3 = j_max_2;
|
||||
m2 = max; i_max_2 = i_max; j_max_2 = j_max;
|
||||
max = Prob[i][j]; i_max = i; j_max = j;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//Highest likelihoods
|
||||
for (int i = 0; i < numHLAlleles; i++){
|
||||
for (int j = 0; j < numHLAlleles; j++){
|
||||
if (i >= j){
|
||||
if (Prob[i][j] == max){
|
||||
out.printf("Highest likelihood: %5.0f in %s and %s; i=%s, j=%s\n",max,HLAnames.get(i),HLAnames.get(j),i,j);
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//2nd Highest likelihoods
|
||||
for (int i = 0; i < numHLAlleles; i++){
|
||||
for (int j = 0; j < numHLAlleles; j++){
|
||||
if (i >= j){
|
||||
if (Prob[i][j] == m2){
|
||||
out.printf("2nd Highest likelihood: %5.0f in %s and %s; i=%s, j=%s\n",m2,HLAnames.get(i),HLAnames.get(j),i,j);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
PrintedOutput = true;
|
||||
//out.printf("Average depth of coverage is: %.2f in %d total coverage over %d sites\n",((double)result.getFirst() / (double)result.getSecond()), result.getFirst(), result.getSecond());
|
||||
}
|
||||
out.printf("\n");
|
||||
out.printf("Highest score: %5.0f in %s and %s\n",max,HLAnames.get(max_i),HLAnames.get(max_j));
|
||||
out.printf("2nd Highest score: %5.0f in %s and %s\n",max_2,HLAnames.get(max_i_2),HLAnames.get(max_j_2));
|
||||
out.printf("3rd Highest score: %5.0f in %s and %s\n",max_3,HLAnames.get(max_i_3),HLAnames.get(max_j_3));
|
||||
//out.printf("Average depth of coverage is: %.2f in %d total coverage over %d sites\n",((double)result.getFirst() / (double)result.getSecond()), result.getFirst(), result.getSecond());
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue