private static final String DNA = "DNA";
+ private static final String RNA = "RNA";
+
/*
* Quick look-up of String value of char 'A' to 'Z'
*/
}
+
/**
* Calculate the consensus symbol(s) for each column in the given range.
*
{
if (sequences[row] == null)
{
- System.err
- .println("WARNING: Consensus skipping null sequence - possible race condition.");
+ System.err.println(
+ "WARNING: Consensus skipping null sequence - possible race condition.");
continue;
}
- char[] seq = sequences[row].getSequence();
- if (seq.length > column)
+ if (sequences[row].getLength() > column)
{
- char c = seq[column];
+ char c = sequences[row].getCharAt(column);
residueCounts.add(c);
if (Comparison.isNucleotide(c))
{
}
/**
+ * Returns the full set of profiles for a hidden Markov model. The underlying
+ * data is the raw probabilities of a residue being emitted at each node,
+ * however the profiles returned by this function contain the percentage
+ * chance of a residue emission.
+ *
+ * @param hmm
+ * @param width
+ * The width of the Profile array (Profiles) to be returned.
+ * @param start
+ * The alignment column on which the first profile is based.
+ * @param end
+ * The alignment column on which the last profile is based.
+ * @param saveFullProfile
+ * Flag for saving the counts for each profile
+ * @param removeBelowBackground
+ * Flag for removing any characters with a match emission probability
+ * less than its background frequency
+ * @return
+ */
+ public static ProfilesI calculateHMMProfiles(final HiddenMarkovModel hmm,
+ int width, int start, int end, boolean saveFullProfile,
+ boolean removeBelowBackground, boolean infoLetterHeight)
+ {
+ ProfileI[] result = new ProfileI[width];
+ int symbolCount = hmm.getNumberOfSymbols();
+ for (int column = start; column < end; column++)
+ {
+ ResidueCount counts = new ResidueCount();
+ for (char symbol : hmm.getSymbols())
+ {
+ int value = getAnalogueCount(hmm, column, symbol,
+ removeBelowBackground, infoLetterHeight);
+ counts.put(symbol, value);
+ }
+ int maxCount = counts.getModalCount();
+ String maxResidue = counts.getResiduesForCount(maxCount);
+ int gapCount = counts.getGapCount();
+ ProfileI profile = new Profile(symbolCount, gapCount, maxCount,
+ maxResidue);
+
+ if (saveFullProfile)
+ {
+ profile.setCounts(counts);
+ }
+
+ result[column] = profile;
+ }
+ return new Profiles(result);
+ }
+
+ /**
* Make an estimate of the profile size we are going to compute i.e. how many
* different characters may be present in it. Overestimating has a cost of
* using more memory than necessary. Underestimating has a cost of needing to
}
/**
+ * Derive the information 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 'ignore below background frequency',
+ * which may in turn result in a change in the derived values.
+ *
+ * @param information
+ * the annotation row to add annotations to
+ * @param profiles
+ * the source information data
+ * @param startCol
+ * start column (inclusive)
+ * @param endCol
+ * end column (exclusive)
+ * @param ignoreGaps
+ * if true, normalise residue percentages
+ * @param showSequenceLogo
+ * if true include all information symbols, else just show modal
+ * residue
+ * @param nseq
+ * number of sequences
+ */
+ public static float completeInformation(AlignmentAnnotation information,
+ ProfilesI profiles, int startCol, int endCol, long nseq,
+ Float currentMax)
+ {
+ // long now = System.currentTimeMillis();
+ if (information == null || information.annotations == null
+ || information.annotations.length < endCol)
+ {
+ /*
+ * called with a bad alignment annotation row
+ * wait for it to be initialised properly
+ */
+ return 0;
+ }
+
+ Float max = 0f;
+
+ for (int i = startCol; i < endCol; i++)
+ {
+ ProfileI profile = profiles.get(i);
+ if (profile == null)
+ {
+ /*
+ * happens if sequences calculated over were
+ * shorter than alignment width
+ */
+ information.annotations[i] = null;
+ return 0;
+ }
+
+ HiddenMarkovModel hmm;
+
+ SequenceI hmmSeq = information.sequenceRef;
+
+ hmm = hmmSeq.getHMM();
+
+ Float value = getInformationContent(i, hmm);
+
+ if (value > max)
+ {
+ max = value;
+ }
+
+ String description = value + " bits";
+ information.annotations[i] = new Annotation(
+ Character.toString(Character
+ .toUpperCase(hmm.getConsensusAtAlignColumn(i))),
+ description, ' ', value);
+ }
+ if (max > currentMax)
+ {
+ information.graphMax = max;
+ return max;
+ }
+ else
+ {
+ information.graphMax = currentMax;
+ return currentMax;
+ }
+ }
+
+ /**
* Derive the gap count annotation row.
*
* @param gaprow
// always set ranges again
gaprow.graphMax = nseq;
gaprow.graphMin = 0;
- double scale = 0.8/nseq;
+ double scale = 0.8 / nseq;
for (int i = startCol; i < endCol; i++)
{
ProfileI profile = profiles.get(i);
String description = "" + gapped;
- gaprow.annotations[i] = new Annotation("", description,
- '\0', gapped, jalview.util.ColorUtils.bleachColour(
- Color.DARK_GRAY, (float) scale * gapped));
+ gaprow.annotations[i] = new Annotation("", description, '\0', gapped,
+ jalview.util.ColorUtils.bleachColour(Color.DARK_GRAY,
+ (float) scale * gapped));
}
}
* <ul>
* <li>the full profile (percentages of all residues present), if
* showSequenceLogo is true, or</li>
- * <li>just the modal (most common) residue(s), if showSequenceLogo is false</li>
+ * <li>just the modal (most common) residue(s), if showSequenceLogo is
+ * false</li>
* </ul>
* Percentages are as a fraction of all sequence, or only ungapped sequences
* if ignoreGaps is true.
String description = null;
if (counts != null && showSequenceLogo)
{
- int normaliseBy = ignoreGaps ? profile.getNonGapped() : profile
- .getHeight();
+ int normaliseBy = ignoreGaps ? profile.getNonGapped()
+ : profile.getHeight();
description = counts.getTooltip(normaliseBy, dp);
}
else
QuickSort.sort(values, symbols);
int nextArrayPos = 2;
int totalPercentage = 0;
- final int divisor = ignoreGaps ? profile.getNonGapped() : profile
- .getHeight();
+ final int divisor = ignoreGaps ? profile.getNonGapped()
+ : profile.getHeight();
/*
* traverse the arrays in reverse order (highest counts first)
{
continue;
}
- List<char[]> codons = MappingUtils
- .findCodonsFor(seq, col, mappings);
+ List<char[]> codons = MappingUtils.findCodonsFor(seq, col,
+ mappings);
for (char[] codon : codons)
{
int codonEncoded = CodingUtils.encodeCodon(codon);
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] == sortedCodonCounts[codons.length - 1])
+ String modalCodon = String
+ .valueOf(CodingUtils.decodeCodon(modalCodonEncoded));
+ if (sortedCodonCounts.length > 1 && sortedCodonCounts[codons.length
+ - 2] == sortedCodonCounts[codons.length - 1])
{
/*
* two or more codons share the modal count
{
if (samePercent.length() > 0)
{
- mouseOver.append(samePercent).append(": ")
- .append(lastPercent).append("% ");
+ mouseOver.append(samePercent).append(": ").append(lastPercent)
+ .append("% ");
}
samePercent.setLength(0);
samePercent.append(codon);
}
/**
+ * Returns the information content at a specified column.
+ *
+ * @param column
+ * Index of the column, starting from 0.
+ * @return
+ */
+ public static float getInformationContent(int column,
+ HiddenMarkovModel hmm)
+ {
+ float informationContent = 0f;
+
+ for (char symbol : hmm.getSymbols())
+ {
+ float freq = 0f;
+ freq = ResidueProperties.backgroundFrequencies
+ .get(hmm.getAlphabetType()).get(symbol);
+ Double hmmProb = hmm.getMatchEmissionProbability(column, symbol);
+ float prob = hmmProb.floatValue();
+ informationContent += prob * (Math.log(prob / freq) / Math.log(2));
+
+ }
+
+ return informationContent;
+ }
+
+ /**
* Produces a HMM profile for a column in an alignment
*
* @param aa
* less than their background frequencies.
* @return
*/
- public static int[] getHMMProfileFor(AlignmentAnnotation aa, int column,
- boolean removeBelowBackground)
+ public static int[] extractHMMProfile(HiddenMarkovModel hmm, int column,
+ boolean removeBelowBackground, boolean infoHeight)
{
- HiddenMarkovModel hmm;
- hmm = aa.getHMM();
if (hmm != null)
{
- String alph = hmm.getAlphabetType();
int size = hmm.getNumberOfSymbols();
char symbols[] = new char[size];
int values[] = new int[size];
{
char symbol = charList.get(i);
symbols[i] = symbol;
- Double value;
-
- value = hmm.getMatchEmissionProbability(column, symbol);
- double freq;
-
- if (AMINO.equals(alph) && removeBelowBackground)
- {
- freq = ResidueProperties.aminoBackgroundFrequencies.get(symbol);
- if (value < freq)
- {
- value = 0d;
- }
- }
- else if (DNA.equals(alph) && removeBelowBackground)
- {
- freq = ResidueProperties.nucleotideBackgroundFrequencies
- .get(symbol);
- if (value < freq)
- {
- value = 0d;
- }
- }
- value = value * 10000;
- values[i] = value.intValue();
- totalCount += value.intValue();
+ int value = getAnalogueCount(hmm, column, symbol,
+ removeBelowBackground, infoHeight);
+ values[i] = value;
+ totalCount += value;
}
QuickSort.sort(values, symbols);
profile[0] = AlignmentAnnotation.SEQUENCE_PROFILE;
profile[1] = size;
- profile[2] = totalCount / 100;
+ profile[2] = 100;
if (totalCount != 0)
{
int arrayPos = 3;
for (int k = size - 1; k >= 0; k--)
{
- Double percentage;
+ Float percentage;
Integer value = values[k];
- percentage = (value.doubleValue() / totalCount.doubleValue())
- * 100d;
+ if (removeBelowBackground)
+ {
+ percentage = (value.floatValue() / totalCount.floatValue())
+ * 100;
+ }
+ else
+ {
+ percentage = value.floatValue() / 100f;
+ }
+ int intPercent = Math.round(percentage);
profile[arrayPos] = symbols[k];
- profile[arrayPos + 1] = percentage.intValue();
+ profile[arrayPos + 1] = intPercent;
arrayPos += 2;
}
}
}
return null;
}
+
+ /**
+ * Converts the emission probability of a residue at a column in the alignment
+ * to a 'count' to allow for processing by the annotation renderer.
+ *
+ * @param hmm
+ * @param column
+ * @param removeBelowBackground
+ * When true, this method returns 0 for any symbols with a match
+ * emission probability less than the background frequency.
+ * @param symbol
+ * @return
+ */
+ static int getAnalogueCount(HiddenMarkovModel hmm, int column,
+ char symbol, boolean removeBelowBackground, boolean infoHeight)
+ {
+ Double value;
+
+ value = hmm.getMatchEmissionProbability(column, symbol);
+ double freq;
+
+ freq = ResidueProperties.backgroundFrequencies
+ .get(hmm.getAlphabetType()).get(symbol);
+ if (value < freq && removeBelowBackground)
+ {
+ return 0;
+ }
+
+ if (infoHeight)
+ {
+ value = value * (Math.log(value / freq) / Math.log(2));
+ }
+
+ value = value * 10000;
+ return Math.round(value.floatValue());
+ }
}
git://source.jalview.org / jalview.git / blobdiff