sequences,
int start, int end, boolean profile)
{
SequenceI[] seqs = new SequenceI[sequences.size()];
int width = 0;
synchronized (sequences)
{
for (int i = 0; i < sequences.size(); i++)
{
seqs[i] = sequences.get(i);
if (seqs[i].getLength() > width)
{
width = seqs[i].getLength();
}
}
Hashtable[] reply = new Hashtable[width];
if (end >= width)
{
end = width;
}
calculate(seqs, start, end, reply, profile);
return reply;
}
}
public static final void calculate(SequenceI[] sequences, int start,
int end, Hashtable[] result, boolean profile)
{
Hashtable residueHash;
int maxCount, nongap, i, j, v;
int jSize = sequences.length;
String maxResidue;
char c = '-';
float percentage;
int[] values = new int[255];
char[] seq;
for (i = start; i < end; i++)
{
residueHash = new Hashtable();
maxCount = 0;
maxResidue = "";
nongap = 0;
values = new int[255];
for (j = 0; j < jSize; j++)
{
if (sequences[j] == null)
{
System.err
.println("WARNING: Consensus skipping null sequence - possible race condition.");
continue;
}
seq = sequences[j].getSequence();
if (seq.length > i)
{
c = seq[i];
if (c == '.' || c == ' ')
{
c = '-';
}
if (c == '-')
{
values['-']++;
continue;
}
else if ('a' <= c && c <= 'z')
{
c += TO_UPPER_CASE;
}
nongap++;
values[c]++;
}
else
{
values['-']++;
}
}
if (jSize == 1)
{
maxResidue = String.valueOf(c);
maxCount = 1;
}
else
{
for (v = 'A'; v <= 'Z'; v++)
{
// TODO why ignore values[v] == 1?
if (values[v] < 1 /* 2 */|| values[v] < maxCount)
{
continue;
}
if (values[v] > maxCount)
{
maxResidue = CHARS[v - 'A'];
}
else if (values[v] == maxCount)
{
maxResidue += CHARS[v - 'A'];
}
maxCount = values[v];
}
}
if (maxResidue.length() == 0)
{
maxResidue = "-";
}
if (profile)
{
// TODO use a 1-dimensional array with jSize, nongap in [0] and [1]
residueHash.put(PROFILE, new int[][]
{ values, new int[]
{ jSize, nongap } });
}
residueHash.put(MAXCOUNT, new Integer(maxCount));
residueHash.put(MAXRESIDUE, maxResidue);
percentage = ((float) maxCount * 100) / jSize;
residueHash.put(PID_GAPS, new Float(percentage));
if (nongap > 0)
{
// calculate for non-gapped too
percentage = ((float) maxCount * 100) / nongap;
}
residueHash.put(PID_NOGAPS, new Float(percentage));
result[i] = residueHash;
}
}
/**
* Compute all or part of the annotation row from the given consensus
* hashtable
*
* @param consensus
* - pre-allocated annotation row
* @param hconsensus
* @param iStart
* @param width
* @param ignoreGapsInConsensusCalculation
* @param includeAllConsSymbols
* @param nseq
*/
public static void completeConsensus(AlignmentAnnotation consensus,
Hashtable[] hconsensus, int iStart, int width,
boolean ignoreGapsInConsensusCalculation,
boolean includeAllConsSymbols, long nseq)
{
completeConsensus(consensus, hconsensus, iStart, width,
ignoreGapsInConsensusCalculation, includeAllConsSymbols, null,
nseq);
}
/**
* Derive the consensus annotations to be added to the alignment for display.
* This does not recompute the raw data, but may be called on a change in
* display options, such as 'show logo', which may in turn result in a change
* in the derived values.
*
* @param consensus
* the annotation row to add annotations to
* @param hconsensus
* the source consensus data
* @param iStart
* start column
* @param width
* end column
* @param ignoreGapsInConsensusCalculation
* if true, use the consensus calculated ignoring gaps
* @param includeAllConsSymbols
* if true include all consensus symbols, else just show modal
* residue
* @param alphabet
* @param nseq
* number of sequences
*/
public static void completeConsensus(AlignmentAnnotation consensus,
Hashtable[] hconsensus, int iStart, int width,
boolean ignoreGapsInConsensusCalculation,
boolean includeAllConsSymbols, char[] alphabet, long nseq)
{
if (consensus == null || consensus.annotations == null
|| consensus.annotations.length < width)
{
// called with a bad alignment annotation row - wait for it to be
// initialised properly
return;
}
final Format fmt = getPercentageFormat(nseq);
for (int i = iStart; i < width; i++)
{
Hashtable hci;
if (i >= hconsensus.length || ((hci = hconsensus[i]) == null))
{
// happens if sequences calculated over were shorter than alignment
// width
consensus.annotations[i] = null;
continue;
}
Float fv = (Float) hci
.get(ignoreGapsInConsensusCalculation ? PID_NOGAPS : PID_GAPS);
if (fv == null)
{
consensus.annotations[i] = null;
// data has changed below us .. give up and
continue;
}
float value = fv.floatValue();
String maxRes = hci.get(AAFrequency.MAXRESIDUE).toString();
StringBuilder mouseOver = new StringBuilder(64);
if (maxRes.length() > 1)
{
mouseOver.append("[").append(maxRes).append("] ");
maxRes = "+";
}
else
{
mouseOver.append(hci.get(AAFrequency.MAXRESIDUE) + " ");
}
int[][] profile = (int[][]) hci.get(AAFrequency.PROFILE);
if (profile != null && includeAllConsSymbols)
{
int sequenceCount = profile[1][0];
int nonGappedCount = profile[1][1];
int normalisedBy = ignoreGapsInConsensusCalculation ? nonGappedCount
: sequenceCount;
mouseOver.setLength(0);
if (alphabet != null)
{
for (int c = 0; c < alphabet.length; c++)
{
float tval = profile[0][alphabet[c]] * 100f / normalisedBy;
mouseOver
.append(((c == 0) ? "" : "; "))
.append(alphabet[c])
.append(" ")
.append(((fmt != null) ? fmt.formDouble(tval) : ((int) tval)))
.append("%");
}
}
else
{
// TODO do this sort once only in calculate()?
// char[][] ca = new char[profile[0].length][];
char[] ca = new char[profile[0].length];
float[] vl = new float[profile[0].length];
for (int c = 0; c < ca.length; c++)
{
ca[c] = (char) c;
// ca[c] = new char[]
// { (char) c };
vl[c] = profile[0][c];
}
QuickSort.sortFloatChar(vl, ca);
for (int p = 0, c = ca.length - 1; profile[0][ca[c]] > 0; c--)
{
final char residue = ca[c];
if (residue != '-')
{
float tval = profile[0][residue] * 100f / normalisedBy;
mouseOver
.append((((p == 0) ? "" : "; ")))
.append(residue)
.append(" ")
.append(((fmt != null) ? fmt.formDouble(tval)
: ((int) tval))).append("%");
p++;
}
}
}
}
else
{
mouseOver.append(
(((fmt != null) ? fmt.formDouble(value) : ((int) value))))
.append("%");
}
consensus.annotations[i] = new Annotation(maxRes,
mouseOver.toString(), ' ',
value);
}
}
/**
* Returns a Format designed to show all significant figures for profile
* percentages. For less than 100 sequences, returns null (the integer
* percentage value will be displayed). For 100-999 sequences, returns "%3.1f"
*
* @param nseq
* @return
*/
protected static Format getPercentageFormat(long nseq)
{
int scale = 0;
while (nseq >= 10)
{
scale++;
nseq /= 10;
}
return scale <= 1 ? null : new Format("%3." + (scale - 1) + "f");
}
/**
* Returns the sorted profile for the given consensus data. The returned array
* contains
*
*
* [profileType, numberOfValues, nonGapCount, charValue1, percentage1, charValue2, percentage2, ...]
* in descending order of percentage value
*
*
* @param hconsensus
* the data table from which to extract and sort values
* @param ignoreGaps
* if true, only non-gapped values are included in percentage
* calculations
* @return
*/
public static int[] extractProfile(Hashtable hconsensus,
boolean ignoreGaps)
{
int[] rtnval = new int[64];
int[][] profile = (int[][]) hconsensus.get(AAFrequency.PROFILE);
if (profile == null)
{
return null;
}
char[] ca = new char[profile[0].length];
float[] vl = new float[profile[0].length];
for (int c = 0; c < ca.length; c++)
{
ca[c] = (char) c;
vl[c] = profile[0][c];
}
QuickSort.sortFloatChar(vl, ca);
int nextArrayPos = 2;
int totalPercentage = 0;
int distinctValuesCount = 0;
final int divisor = profile[1][ignoreGaps ? 1 : 0];
for (int c = ca.length - 1; profile[0][ca[c]] > 0; c--)
{
if (ca[c] != '-')
{
rtnval[nextArrayPos++] = ca[c];
final int percentage = (int) (profile[0][ca[c]] * 100f / divisor);
rtnval[nextArrayPos++] = percentage;
totalPercentage += percentage;
distinctValuesCount++;
}
}
rtnval[0] = distinctValuesCount;
rtnval[1] = totalPercentage;
int[] result = new int[rtnval.length + 1];
result[0] = AlignmentAnnotation.SEQUENCE_PROFILE;
System.arraycopy(rtnval, 0, result, 1, rtnval.length);
return result;
}
/**
* Extract a sorted extract of cDNA codon profile data. The returned array
* contains
*
*
* [profileType, numberOfValues, totalCount, charValue1, percentage1, charValue2, percentage2, ...]
* in descending order of percentage value, where the character values encode codon triplets
*
*
* @param hashtable
* @return
*/
public static int[] extractCdnaProfile(Hashtable hashtable, boolean ignoreGaps)
{
// this holds #seqs, #ungapped, and then codon count, indexed by encoded
// codon triplet
int[] codonCounts = (int[]) hashtable.get(PROFILE);
int[] sortedCounts = new int[codonCounts.length - 2];
System.arraycopy(codonCounts, 2, sortedCounts, 0,
codonCounts.length - 2);
int[] result = new int[3 + 2 * sortedCounts.length];
// first value is just the type of profile data
result[0] = AlignmentAnnotation.CDNA_PROFILE;
char[] codons = new char[sortedCounts.length];
for (int i = 0; i < codons.length; i++)
{
codons[i] = (char) i;
}
QuickSort.sortIntChar(sortedCounts, codons);
int totalPercentage = 0;
int distinctValuesCount = 0;
int j = 3;
int divisor = ignoreGaps ? codonCounts[1] : codonCounts[0];
for (int i = codons.length - 1; i >= 0; i--)
{
final int codonCount = sortedCounts[i];
if (codonCount == 0)
{
break; // nothing else of interest here
}
distinctValuesCount++;
result[j++] = codons[i];
final int percentage = codonCount * 100 / divisor;
result[j++] = percentage;
totalPercentage += percentage;
}
result[2] = totalPercentage;
/*
* Just return the non-zero values
*/
// todo next value is redundant if we limit the array to non-zero counts
result[1] = distinctValuesCount;
return Arrays.copyOfRange(result, 0, j);
}
/**
* Compute a consensus for the cDNA coding for a protein alignment.
*
* @param alignment
* the protein alignment (which should hold mappings to cDNA
* sequences)
* @param hconsensus
* the consensus data stores to be populated (one per column)
* @param mappings
* @param col0 first column
* @param co11 last column
*/
public static void calculateCdna(AlignmentI alignment,
Set mappings, Hashtable[] hconsensus, int col0,
int col1) {
final char gapCharacter = alignment.getGapCharacter();
for (int col = col0; col < col1; col++) {
// todo would prefer a Java bean for consensus data
Hashtable columnHash = new Hashtable();
// #seqs, #ungapped seqs, counts indexed by (codon encoded + 1)
int[] codonCounts = new int[66];
codonCounts[0] = alignment.getSequences().size();
int ungappedCount = 0;
for (SequenceI seq : alignment.getSequences()) {
if (seq.getCharAt(col) == gapCharacter) {
continue;
}
char[] codon = MappingUtils.findCodonFor(seq, col, mappings);
int codonEncoded = CodingUtils.encodeCodon(codon);
if (codonEncoded >= 0) {
codonCounts[codonEncoded + 2]++;
ungappedCount++;
}
}
codonCounts[1] = ungappedCount;
// todo: sort values here, save counts and codons?
columnHash.put(PROFILE, codonCounts);
hconsensus[col] = columnHash;
}
}
/**
* Derive displayable cDNA consensus annotation from computed consensus data.
*
* @param consensusAnnotation
* the annotation row to be populated for display
* @param consensusData
* the computed consensus data
* @param showProfileLogo
* if true show all symbols present at each position, else only the
* modal value
* @param nseqs
* the number of sequences in the alignment
*/
public static void completeCdnaConsensus(
AlignmentAnnotation consensusAnnotation,
Hashtable[] consensusData, boolean showProfileLogo, int nseqs)
{
if (consensusAnnotation == null
|| consensusAnnotation.annotations == null
|| consensusAnnotation.annotations.length < consensusData.length)
{
// called with a bad alignment annotation row - wait for it to be
// initialised properly
return;
}
// ensure codon triplet scales with font size
consensusAnnotation.scaleColLabel = true;
for (int col = 0; col < consensusData.length; col++)
{
Hashtable hci = consensusData[col];
if (hci == null)
{
// gapped protein column?
continue;
}
// array holds #seqs, #ungapped, then codon counts indexed by codon
final int[] codonCounts = (int[]) hci.get(PROFILE);
int totalCount = 0;
/*
* First pass - get total count and find the highest
*/
final char[] codons = new char[codonCounts.length - 2];
for (int j = 2; j < codonCounts.length; j++)
{
final int codonCount = codonCounts[j];
codons[j - 2] = (char) (j - 2);
totalCount += codonCount;
}
/*
* Sort array of encoded codons by count ascending - so the modal value
* goes to the end; start by copying the count (dropping the first value)
*/
int[] sortedCodonCounts = new int[codonCounts.length - 2];
System.arraycopy(codonCounts, 2, sortedCodonCounts, 0,
codonCounts.length - 2);
QuickSort.sortIntChar(sortedCodonCounts, codons);
int modalCodonEncoded = codons[codons.length - 1];
int modalCodonCount = sortedCodonCounts[codons.length - 1];
String modalCodon = String.valueOf(CodingUtils
.decodeCodon(modalCodonEncoded));
if (sortedCodonCounts.length > 1
&& sortedCodonCounts[codons.length - 2] == modalCodonEncoded)
{
modalCodon = "+";
}
float pid = sortedCodonCounts[sortedCodonCounts.length - 1] * 100
/ (float) totalCount;
/*
* todo ? Replace consensus hashtable with sorted arrays of codons and
* counts (non-zero only). Include total count in count array [0].
*/
/*
* Scan sorted array backwards for most frequent values first. Show
* repeated values compactly.
*/
StringBuilder mouseOver = new StringBuilder(32);
StringBuilder samePercent = new StringBuilder();
String percent = null;
String lastPercent = null;
Format fmt = getPercentageFormat(nseqs);
for (int j = codons.length - 1; j >= 0; j--)
{
int codonCount = sortedCodonCounts[j];
if (codonCount == 0)
{
/*
* remaining codons are 0% - ignore, but finish off the last one if
* necessary
*/
if (samePercent.length() > 0)
{
mouseOver.append(samePercent).append(": ").append(percent)
.append("% ");
}
break;
}
int codonEncoded = codons[j];
final int pct = codonCount * 100 / totalCount;
String codon = String
.valueOf(CodingUtils.decodeCodon(codonEncoded));
percent = fmt == null ? Integer.toString(pct) : fmt
.formLong(pct);
if (showProfileLogo || codonCount == modalCodonCount)
{
if (percent.equals(lastPercent) && j > 0)
{
samePercent.append(samePercent.length() == 0 ? "" : ", ");
samePercent.append(codon);
}
else
{
if (samePercent.length() > 0)
{
mouseOver.append(samePercent).append(": ")
.append(lastPercent)
.append("% ");
}
samePercent.setLength(0);
samePercent.append(codon);
}
lastPercent = percent;
}
}
consensusAnnotation.annotations[col] = new Annotation(modalCodon,
mouseOver.toString(), ' ', pid);
}
}
}