list,
int start, int end)
{
@@ -81,18 +107,13 @@ public class AAFrequency
}
public static final void calculate(SequenceI[] sequences, int start,
- int end, Hashtable[] result)
- {
- calculate(sequences, start, end, result, false);
- }
-
- public static final void calculate(SequenceI[] sequences, int start,
int end, Hashtable[] result, boolean profile)
{
Hashtable residueHash;
- int maxCount, nongap, i, j, v, jSize = sequences.length;
+ int maxCount, nongap, i, j, v;
+ int jSize = sequences.length;
String maxResidue;
- char c='-';
+ char c = '-';
float percentage;
int[] values = new int[255];
@@ -106,7 +127,7 @@ public class AAFrequency
maxResidue = "";
nongap = 0;
values = new int[255];
-
+
for (j = 0; j < jSize; j++)
{
if (sequences[j] == null)
@@ -132,7 +153,7 @@ public class AAFrequency
}
else if ('a' <= c && c <= 'z')
{
- c -= 32; // ('a' - 'A');
+ c += TO_UPPER_CASE;
}
nongap++;
@@ -144,27 +165,31 @@ public class AAFrequency
values['-']++;
}
}
- if (jSize==1)
+ if (jSize == 1)
{
maxResidue = String.valueOf(c);
- maxCount=1;
- } else {for (v = 'A'; v < 'Z'; v++)
+ maxCount = 1;
+ }
+ else
{
- if (values[v] < 2 || values[v] < maxCount)
+ for (v = 'A'; v <= 'Z'; v++)
{
- continue;
- }
+ // TODO why ignore values[v] == 1?
+ if (values[v] < 1 /* 2 */|| values[v] < maxCount)
+ {
+ continue;
+ }
- if (values[v] > maxCount)
- {
- maxResidue = String.valueOf((char) v);
- }
- else if (values[v] == maxCount)
- {
- maxResidue += String.valueOf((char) v);
+ if (values[v] > maxCount)
+ {
+ maxResidue = CHARS[v - 'A'];
+ }
+ else if (values[v] == maxCount)
+ {
+ maxResidue += CHARS[v - 'A'];
+ }
+ maxCount = values[v];
}
- maxCount = values[v];
- }
}
if (maxResidue.length() == 0)
{
@@ -172,6 +197,7 @@ public class AAFrequency
}
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 } });
@@ -182,12 +208,13 @@ public class AAFrequency
percentage = ((float) maxCount * 100) / jSize;
residueHash.put(PID_GAPS, new Float(percentage));
- if (nongap>0) {
+ if (nongap > 0)
+ {
// calculate for non-gapped too
percentage = ((float) maxCount * 100) / nongap;
}
residueHash.put(PID_NOGAPS, new Float(percentage));
-
+
result[i] = residueHash;
}
}
@@ -203,7 +230,7 @@ public class AAFrequency
* @param width
* @param ignoreGapsInConsensusCalculation
* @param includeAllConsSymbols
- * @param nseq
+ * @param nseq
*/
public static void completeConsensus(AlignmentAnnotation consensus,
Hashtable[] hconsensus, int iStart, int width,
@@ -211,17 +238,38 @@ public class AAFrequency
boolean includeAllConsSymbols, long nseq)
{
completeConsensus(consensus, hconsensus, iStart, width,
- ignoreGapsInConsensusCalculation, includeAllConsSymbols, null, nseq); // new
- // char[]
- // { 'A', 'C', 'G', 'T', 'U' });
+ 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)
{
- float tval, value;
if (consensus == null || consensus.annotations == null
|| consensus.annotations.length < width)
{
@@ -229,23 +277,9 @@ public class AAFrequency
// initialised properly
return;
}
- String fmtstr="%3.1f";
- int precision=0;
- while (nseq>=10) {
- precision++;
- nseq/=10;
- }
- final Format fmt;
- if (precision>1)
- {
- //if (precision>2)
- {
- fmtstr = "%"+(2+precision)+"."+(precision)+"f";
- }
- fmt = new Format(fmtstr);
- } else {
- fmt = null;
- }
+
+ final Format fmt = getPercentageFormat(nseq);
+
for (int i = iStart; i < width; i++)
{
Hashtable hci;
@@ -256,116 +290,406 @@ public class AAFrequency
consensus.annotations[i] = null;
continue;
}
- value = 0;
- Float fv;
- if (ignoreGapsInConsensusCalculation)
- {
- fv = (Float) hci.get(AAFrequency.PID_NOGAPS);
- }
- else
- {
- fv = (Float) hci.get(AAFrequency.PID_GAPS);
- }
+ 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;
}
- value = fv.floatValue();
+ float value = fv.floatValue();
String maxRes = hci.get(AAFrequency.MAXRESIDUE).toString();
- String mouseOver = hci.get(AAFrequency.MAXRESIDUE) + " ";
+ StringBuilder mouseOver = new StringBuilder(64);
if (maxRes.length() > 1)
{
- mouseOver = "[" + maxRes + "] ";
+ mouseOver.append("[").append(maxRes).append("] ");
maxRes = "+";
}
+ else
+ {
+ mouseOver.append(hci.get(AAFrequency.MAXRESIDUE) + " ");
+ }
int[][] profile = (int[][]) hci.get(AAFrequency.PROFILE);
if (profile != null && includeAllConsSymbols)
{
- mouseOver = "";
+ 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++)
{
- tval = profile[0][alphabet[c]] * 100f
- / profile[1][ignoreGapsInConsensusCalculation ? 1 : 0];
- mouseOver += ((c == 0) ? "" : "; ") + alphabet[c] + " "
- + ((fmt!=null) ? fmt.form(tval) : ((int) tval)) + "%";
+ float tval = profile[0][alphabet[c]] * 100f / normalisedBy;
+ mouseOver
+ .append(((c == 0) ? "" : "; "))
+ .append(alphabet[c])
+ .append(" ")
+ .append(((fmt != null) ? fmt.form(tval) : ((int) tval)))
+ .append("%");
}
}
else
{
- Object[] ca = new Object[profile[0].length];
+ // 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] = new char[]
- { (char) c };
+ ca[c] = (char) c;
+ // ca[c] = new char[]
+ // { (char) c };
vl[c] = profile[0][c];
}
- ;
- jalview.util.QuickSort.sort(vl, ca);
- for (int p = 0, c = ca.length - 1; profile[0][((char[]) ca[c])[0]] > 0; c--)
+ QuickSort.sort(vl, ca);
+ for (int p = 0, c = ca.length - 1; profile[0][ca[c]] > 0; c--)
{
- if (((char[]) ca[c])[0] != '-')
+ final char residue = ca[c];
+ if (residue != '-')
{
- tval = profile[0][((char[]) ca[c])[0]]
- * 100f
- / profile[1][ignoreGapsInConsensusCalculation ? 1 : 0];
- mouseOver += ((p == 0) ? "" : "; ") + ((char[]) ca[c])[0]
- + " " + ((fmt!=null) ? fmt.form(tval) : ((int) tval)) + "%";
+ float tval = profile[0][residue] * 100f / normalisedBy;
+ mouseOver
+ .append((((p == 0) ? "" : "; ")))
+ .append(residue)
+ .append(" ")
+ .append(((fmt != null) ? fmt.form(tval)
+ : ((int) tval))).append("%");
p++;
-
}
}
-
}
}
else
{
- mouseOver += ((fmt!=null) ? fmt.form(value) : ((int) value)) + "%";
+ mouseOver.append(
+ (((fmt != null) ? fmt.form(value) : ((int) value))))
+ .append("%");
}
- consensus.annotations[i] = new Annotation(maxRes, mouseOver, ' ',
+ consensus.annotations[i] = new Annotation(maxRes,
+ mouseOver.toString(), ' ',
value);
}
}
/**
- * get the sorted profile for the given position of the consensus
+ * 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 ignoreGapsInConsensusCalculation)
+ boolean ignoreGaps)
{
int[] rtnval = new int[64];
int[][] profile = (int[][]) hconsensus.get(AAFrequency.PROFILE);
if (profile == null)
+ {
return null;
- Object[] ca = new Object[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] = new char[]
- { (char) c };
+ ca[c] = (char) c;
vl[c] = profile[0][c];
}
- ;
- jalview.util.QuickSort.sort(vl, ca);
- rtnval[0] = 2;
- rtnval[1] = 0;
- for (int c = ca.length - 1; profile[0][((char[]) ca[c])[0]] > 0; c--)
+ QuickSort.sort(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.sort(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)
+ */
+ public static void calculateCdna(AlignmentI alignment,
+ Hashtable[] hconsensus)
+ {
+ final char gapCharacter = alignment.getGapCharacter();
+ Set mappings = alignment.getCodonFrames();
+ if (mappings == null || mappings.isEmpty())
{
- if (((char[]) ca[c])[0] != '-')
+ return;
+ }
+
+ int cols = alignment.getWidth();
+ for (int col = 0; col < cols; 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())
{
- rtnval[rtnval[0]++] = ((char[]) ca[c])[0];
- rtnval[rtnval[0]] = (int) (profile[0][((char[]) ca[c])[0]] * 100f / profile[1][ignoreGapsInConsensusCalculation ? 1
- : 0]);
- rtnval[1] += rtnval[rtnval[0]++];
+ 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.sort(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
+ .form(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);
}
- return rtnval;
}
}