import jalview.datamodel.AlignmentAnnotation;
import jalview.datamodel.AlignmentI;
import jalview.datamodel.Annotation;
+import jalview.datamodel.HiddenMarkovModel;
import jalview.datamodel.Profile;
import jalview.datamodel.ProfileI;
import jalview.datamodel.Profiles;
import jalview.datamodel.ResidueCount.SymbolCounts;
import jalview.datamodel.SequenceI;
import jalview.ext.android.SparseIntArray;
+import jalview.schemes.ResidueProperties;
import jalview.util.Comparison;
import jalview.util.Format;
import jalview.util.MappingUtils;
* 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";
-
- /*
- * 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)
}
/**
+ * 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 removeBelowBackground
+ * 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 removeBelowBackground,
+ boolean infoLetterHeight)
+ {
+ ProfileI[] result = new ProfileI[width];
+ char[] symbols = hmm.getSymbols().toCharArray();
+ int symbolCount = symbols.length;
+ for (int column = start; column < end; column++)
+ {
+ ResidueCount counts = new ResidueCount();
+ for (char symbol : symbols)
+ {
+ 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);
+ 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 gap count annotation row.
+ * 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
+ */
+ public static float completeInformation(AlignmentAnnotation information,
+ ProfilesI profiles, int startCol, int endCol)
+ {
+ // long now = System.currentTimeMillis();
+ if (information == null || information.annotations == null)
+ {
+ /*
+ * called with a bad alignment annotation row
+ * wait for it to be initialised properly
+ */
+ return 0;
+ }
+
+ float max = 0f;
+ SequenceI hmmSeq = information.sequenceRef;
+
+ int seqLength = hmmSeq.getLength();
+ if (information.annotations.length < seqLength)
+ {
+ return 0;
+ }
+
+ HiddenMarkovModel hmm = hmmSeq.getHMM();
+
+ for (int column = startCol; column < endCol; column++)
+ {
+ if (column >= seqLength)
+ {
+ // hmm consensus sequence is shorter than the alignment
+ break;
+ }
+
+ float value = hmm.getInformationContent(column);
+ boolean isNaN = Float.isNaN(value);
+ if (!isNaN)
+ {
+ max = Math.max(max, value);
+ }
+
+ String description = isNaN ? null
+ : String.format("%.4f bits", value);
+ information.annotations[column] = new Annotation(
+ Character.toString(
+ Character.toUpperCase(hmmSeq.getCharAt(column))),
+ description, ' ', value);
+ }
+
+ information.graphMax = max;
+ return max;
+ }
+
+ /**
+ * 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));
}
return result;
}
+
/**
* Extract a sorted extract of cDNA codon profile data. The returned array
* contains
}
return scale;
}
+
+ /**
+ * Returns the sorted HMM profile for the given column of the alignment. The
+ * returned array contains
+ *
+ * <pre>
+ * [profileType=0, numberOfValues, 100, charValue1, percentage1, charValue2, percentage2, ...]
+ * in descending order of percentage value
+ * </pre>
+ *
+ * @param hmm
+ * @param column
+ * @param removeBelowBackground
+ * 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)
+ {
+ 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 = alphabet.charAt(i);
+ symbols[i] = symbol;
+ int value = getAnalogueCount(hmm, column, symbol,
+ removeBelowBackground, infoHeight);
+ values[i] = value;
+ totalCount += value;
+ }
+
+ /*
+ * sort symbols by increasing emission probability
+ */
+ QuickSort.sort(values, symbols);
+
+ int[] profile = new int[3 + size * 2];
+
+ profile[0] = AlignmentAnnotation.SEQUENCE_PROFILE;
+ profile[1] = size;
+ profile[2] = 100;
+
+ /*
+ * order symbol/count profile by decreasing emission probability
+ */
+ if (totalCount != 0)
+ {
+ int arrayPos = 3;
+ for (int k = size - 1; k >= 0; k--)
+ {
+ Float percentage;
+ int value = values[k];
+ if (removeBelowBackground)
+ {
+ 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;
+ }
+
+ /**
+ * Converts the emission probability of a residue at a column in the alignment
+ * to a 'count', suitable for rendering as an annotation value
+ *
+ * @param hmm
+ * @param column
+ * @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 = hmm.getMatchEmissionProbability(column, symbol);
+ double freq = ResidueProperties.backgroundFrequencies
+ .get(hmm.getAlphabetType()).get(symbol);
+ if (value < freq && removeBelowBackground)
+ {
+ return 0;
+ }
+
+ if (infoHeight)
+ {
+ value = value * (Math.log(value / freq) / LOG2);
+ }
+
+ value = value * 10000d;
+ return Math.round((float) value);
+ }
}
git://source.jalview.org / jalview.git / blobdiff