* This class is used extensively in calculating alignment colourschemes that
* depend on the amount of conservation in each alignment column.
*
- * @author $author$
- * @version $Revision$
*/
public class AAFrequency
{
- public static final String PROFILE = "P";
-
- private static final String AMINO = "amino";
-
- private static final String DNA = "DNA";
-
- private static final String RNA = "RNA";
-
- /*
- * Quick look-up of String value of char 'A' to 'Z'
- */
- private static final String[] CHARS = new String['Z' - 'A' + 1];
+ private static final double LOG2 = Math.log(2);
- static
- {
- for (char c = 'A'; c <= 'Z'; c++)
- {
- CHARS[c - 'A'] = String.valueOf(c);
- }
- }
+ public static final String PROFILE = "P";
public static final ProfilesI calculate(List<SequenceI> list, int start,
int end)
}
}
-
-
/**
* Calculate the consensus symbol(s) for each column in the given range.
*
"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))
{
* 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
+ * if true, symbols with a match emission probability less than
+ * background frequency are ignored
* @return
*/
public static ProfilesI calculateHMMProfiles(final HiddenMarkovModel hmm,
- int width, int start, int end, boolean saveFullProfile,
- boolean removeBelowBackground, boolean infoLetterHeight)
+ int width, int start, int end, boolean removeBelowBackground,
+ boolean infoLetterHeight)
{
ProfileI[] result = new ProfileI[width];
- int symbolCount = hmm.getNumberOfSymbols();
+ char[] symbols = hmm.getSymbols().toCharArray();
+ int symbolCount = symbols.length;
for (int column = start; column < end; column++)
{
ResidueCount counts = new ResidueCount();
- for (char symbol : hmm.getSymbols())
+ for (char symbol : symbols)
{
int value = getAnalogueCount(hmm, column, symbol,
removeBelowBackground, infoLetterHeight);
int gapCount = counts.getGapCount();
ProfileI profile = new Profile(symbolCount, gapCount, maxCount,
maxResidue);
-
- if (saveFullProfile)
- {
- profile.setCounts(counts);
- }
+ profile.setCounts(counts);
result[column] = profile;
}
* @param endCol
* end column (exclusive)
* @param ignoreGaps
- * if true, normalise residue percentages
+ * 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)
+ ProfilesI profiles, int startCol, int endCol)
{
// long now = System.currentTimeMillis();
- if (information == null || information.annotations == null
- || information.annotations.length < endCol)
+ if (information == null || information.annotations == null)
{
/*
* called with a bad alignment annotation row
return 0;
}
- Float max = 0f;
+ float max = 0f;
+ SequenceI hmmSeq = information.sequenceRef;
- for (int i = startCol; i < endCol; i++)
+ int seqLength = hmmSeq.getLength();
+ if (information.annotations.length < seqLength)
{
- ProfileI profile = profiles.get(i);
- if (profile == null)
+ return 0;
+ }
+
+ HiddenMarkovModel hmm = hmmSeq.getHMM();
+
+ for (int column = startCol; column < endCol; column++)
+ {
+ if (column >= seqLength)
{
- /*
- * happens if sequences calculated over were
- * shorter than alignment width
- */
- information.annotations[i] = null;
- return 0;
+ // hmm consensus sequence is shorter than the alignment
+ break;
}
-
- HiddenMarkovModel hmm;
-
- SequenceI hmmSeq = information.sequenceRef;
-
- hmm = hmmSeq.getHMM();
- Float value = getInformationContent(i, hmm);
-
- if (value > max)
+ float value = hmm.getInformationContent(column);
+ boolean isNaN = Float.isNaN(value);
+ if (!isNaN)
{
- max = value;
+ max = Math.max(max, value);
}
- String description = value + " bits";
- information.annotations[i] = new Annotation(
- Character.toString(Character
- .toUpperCase(hmm.getConsensusAtAlignColumn(i))),
+ String description = isNaN ? null
+ : String.format("%.4f bits", value);
+ information.annotations[column] = new Annotation(
+ Character.toString(
+ Character.toUpperCase(hmmSeq.getCharAt(column))),
description, ' ', value);
}
- if (max > currentMax)
- {
- information.graphMax = max;
- return max;
- }
- else
- {
- information.graphMax = currentMax;
- return currentMax;
- }
+
+ information.graphMax = max;
+ return max;
}
/**
- * Derive the gap count annotation row.
+ * Derive the occupancy count annotation
*
- * @param gaprow
+ * @param occupancy
* the annotation row to add annotations to
* @param profiles
* the source consensus data
* @param endCol
* end column (exclusive)
*/
- public static void completeGapAnnot(AlignmentAnnotation gaprow,
+ public static void completeGapAnnot(AlignmentAnnotation occupancy,
ProfilesI profiles, int startCol, int endCol, long nseq)
{
- if (gaprow == null || gaprow.annotations == null
- || gaprow.annotations.length < endCol)
+ if (occupancy == null || occupancy.annotations == null
+ || occupancy.annotations.length < endCol)
{
/*
* called with a bad alignment annotation row
return;
}
// always set ranges again
- gaprow.graphMax = nseq;
- gaprow.graphMin = 0;
+ occupancy.graphMax = nseq;
+ occupancy.graphMin = 0;
double scale = 0.8 / nseq;
for (int i = startCol; i < endCol; i++)
{
* happens if sequences calculated over were
* shorter than alignment width
*/
- gaprow.annotations[i] = null;
+ occupancy.annotations[i] = null;
return;
}
String description = "" + gapped;
- gaprow.annotations[i] = new Annotation("", description, '\0', gapped,
+ occupancy.annotations[i] = new Annotation("", description, '\0',
+ gapped,
jalview.util.ColorUtils.bleachColour(Color.DARK_GRAY,
(float) scale * gapped));
}
}
/**
- * Returns the information content at a specified column.
+ * Returns the sorted HMM profile for the given column of the alignment. The
+ * returned array contains
*
- * @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
+ * <pre>
+ * [profileType=0, numberOfValues, 100, charValue1, percentage1, charValue2, percentage2, ...]
+ * in descending order of percentage value
+ * </pre>
*
- * @param aa
- * Alignment annotation for which the profile is being calculated.
+ * @param hmm
* @param column
- * Column in the alignment the profile is being made for.
* @param removeBelowBackground
- * Boolean indicating whether to ignore residues with probabilities
- * less than their background frequencies.
+ * if true, ignores residues with probability less than their
+ * background frequency
+ * @param infoHeight
+ * if true, uses the log ratio 'information' measure to scale the
+ * value
* @return
*/
public static int[] extractHMMProfile(HiddenMarkovModel hmm, int column,
boolean removeBelowBackground, boolean infoHeight)
{
-
- if (hmm != null)
+ if (hmm == null)
{
- int size = hmm.getNumberOfSymbols();
- char symbols[] = new char[size];
- int values[] = new int[size];
- List<Character> charList = hmm.getSymbols();
- Integer totalCount = 0;
+ return null;
+ }
+ String alphabet = hmm.getSymbols();
+ int size = alphabet.length();
+ char symbols[] = new char[size];
+ int values[] = new int[size];
+ int totalCount = 0;
- for (int i = 0; i < size; i++)
- {
- char symbol = charList.get(i);
- symbols[i] = symbol;
- int value = getAnalogueCount(hmm, column, symbol,
- removeBelowBackground, infoHeight);
- values[i] = value;
- totalCount += value;
- }
+ for (int i = 0; i < size; i++)
+ {
+ char symbol = alphabet.charAt(i);
+ symbols[i] = symbol;
+ int value = getAnalogueCount(hmm, column, symbol,
+ removeBelowBackground, infoHeight);
+ values[i] = value;
+ totalCount += value;
+ }
- QuickSort.sort(values, symbols);
+ /*
+ * sort symbols by increasing emission probability
+ */
+ QuickSort.sort(values, symbols);
- int[] profile = new int[3 + size * 2];
+ int[] profile = new int[3 + size * 2];
- profile[0] = AlignmentAnnotation.SEQUENCE_PROFILE;
- profile[1] = size;
- profile[2] = 100;
+ profile[0] = AlignmentAnnotation.SEQUENCE_PROFILE;
+ profile[1] = size;
+ profile[2] = 100;
- if (totalCount != 0)
+ /*
+ * order symbol/count profile by decreasing emission probability
+ */
+ if (totalCount != 0)
+ {
+ int arrayPos = 3;
+ for (int k = size - 1; k >= 0; k--)
{
- int arrayPos = 3;
- for (int k = size - 1; k >= 0; k--)
+ Float percentage;
+ int value = values[k];
+ if (removeBelowBackground)
{
- Float percentage;
- Integer value = values[k];
- 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] = intPercent;
- arrayPos += 2;
+ percentage = ((float) value) / totalCount * 100f;
+ }
+ else
+ {
+ percentage = value / 100f;
}
+ int intPercent = Math.round(percentage);
+ profile[arrayPos] = symbols[k];
+ profile[arrayPos + 1] = intPercent;
+ arrayPos += 2;
}
- return profile;
}
- return null;
+ return profile;
}
/**
* Converts the emission probability of a residue at a column in the alignment
- * to a 'count' to allow for processing by the annotation renderer.
+ * to a 'count', suitable for rendering as an annotation value
*
* @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
+ * @param removeBelowBackground
+ * if true, returns 0 for any symbol with a match emission
+ * probability less than the background frequency
+ * @infoHeight if true, uses the log ratio 'information content' to scale the
+ * value
* @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
+ double value = hmm.getMatchEmissionProbability(column, symbol);
+ double freq = ResidueProperties.backgroundFrequencies
.get(hmm.getAlphabetType()).get(symbol);
if (value < freq && removeBelowBackground)
{
if (infoHeight)
{
- value = value * (Math.log(value / freq) / Math.log(2));
+ value = value * (Math.log(value / freq) / LOG2);
}
- value = value * 10000;
- return Math.round(value.floatValue());
+ value = value * 10000d;
+ return Math.round((float) value);
}
}
git://source.jalview.org / jalview.git / blobdiff