import jalview.datamodel.AlignmentAnnotation;
import jalview.datamodel.Annotation;
+import jalview.datamodel.Profile;
import jalview.datamodel.ProfileI;
import jalview.datamodel.ProfilesI;
+import jalview.datamodel.ResidueCount;
import jalview.datamodel.Sequence;
import jalview.datamodel.SequenceI;
import jalview.gui.JvOptionPane;
+import java.util.Hashtable;
+
import org.testng.annotations.BeforeClass;
import org.testng.annotations.Test;
SequenceI seq4 = new Sequence("Seq4", "CA--t");
SequenceI[] seqs = new SequenceI[] { seq1, seq2, seq3, seq4 };
int width = seq1.getLength();
- ProfilesI result = AAFrequency.calculate(seqs, width, 0, width,
- false);
+ ProfilesI result = AAFrequency.calculate(seqs, width, 0, width, false);
// col 0 is 100% C
ProfileI col = result.get(0);
SequenceI seq4 = new Sequence("Seq4", "CA-t");
SequenceI[] seqs = new SequenceI[] { seq1, seq2, seq3, seq4 };
int width = seq1.getLength();
- ProfilesI result = AAFrequency.calculate(seqs, width, 0, width,
- true);
+ ProfilesI result = AAFrequency.calculate(seqs, width, 0, width, true);
ProfileI profile = result.get(0);
assertEquals(4, profile.getCounts().getCount('C'));
AlignmentAnnotation consensus = new AlignmentAnnotation("Consensus",
"PID", new Annotation[width]);
- AAFrequency
- .completeConsensus(consensus, profiles, 0, 5, false, true, 4);
+ AAFrequency.completeConsensus(consensus, profiles, 0, 5, false, true,
+ 4);
Annotation ann = consensus.annotations[0];
assertEquals("C 100%", ann.description);
SequenceI[] seqs = new SequenceI[] { seq1, seq2, seq3, seq4 };
int width = seq1.getLength();
ProfilesI profiles = AAFrequency.calculate(seqs, width, 0, width, true);
-
+
AlignmentAnnotation consensus = new AlignmentAnnotation("Consensus",
"PID", new Annotation[width]);
- AAFrequency
- .completeConsensus(consensus, profiles, 0, 5, true, false, 4);
-
+ AAFrequency.completeConsensus(consensus, profiles, 0, 5, true, false,
+ 4);
+
Annotation ann = consensus.annotations[0];
assertEquals("C 100%", ann.description);
assertEquals("C", ann.displayCharacter);
assertEquals("T 75%", ann.description);
assertEquals("T", ann.displayCharacter);
}
+
+ /**
+ * Test to include rounding down of a non-zero count to 0% (JAL-3202)
+ */
+ @Test(groups = { "Functional" })
+ public void testExtractProfile()
+ {
+ /*
+ * 200 sequences of which 30 gapped (170 ungapped)
+ * max count 70 for modal residue 'G'
+ */
+ ProfileI profile = new Profile(200, 30, 70, "G");
+ ResidueCount counts = new ResidueCount();
+ counts.put('G', 70);
+ counts.put('R', 60);
+ counts.put('L', 38);
+ counts.put('H', 2);
+ profile.setCounts(counts);
+
+ /*
+ * [0, noOfValues, totalPercent, char1, count1, ...]
+ * G: 70/170 = 41.2 = 41
+ * R: 60/170 = 35.3 = 35
+ * L: 38/170 = 22.3 = 22
+ * H: 2/170 = 1
+ * total (rounded) percentages = 99
+ */
+ int[] extracted = AAFrequency.extractProfile(profile, true);
+ int[] expected = new int[] { 0, 4, 99, 'G', 41, 'R', 35, 'L', 22, 'H',
+ 1 };
+ org.testng.Assert.assertEquals(extracted, expected);
+
+ /*
+ * add some counts of 1; these round down to 0% and should be discarded
+ */
+ counts.put('G', 68); // 68/170 = 40% exactly (percentages now total 98)
+ counts.put('Q', 1);
+ counts.put('K', 1);
+ extracted = AAFrequency.extractProfile(profile, true);
+ expected = new int[] { 0, 4, 98, 'G', 40, 'R', 35, 'L', 22, 'H', 1 };
+ org.testng.Assert.assertEquals(extracted, expected);
+
+ }
+
+ /**
+ * Tests for the profile calculation where gaps are included i.e. the
+ * denominator is the total number of sequences in the column
+ */
+ @Test(groups = { "Functional" })
+ public void testExtractProfile_countGaps()
+ {
+ /*
+ * 200 sequences of which 30 gapped (170 ungapped)
+ * max count 70 for modal residue 'G'
+ */
+ ProfileI profile = new Profile(200, 30, 70, "G");
+ ResidueCount counts = new ResidueCount();
+ counts.put('G', 70);
+ counts.put('R', 60);
+ counts.put('L', 38);
+ counts.put('H', 2);
+ profile.setCounts(counts);
+
+ /*
+ * [0, noOfValues, totalPercent, char1, count1, ...]
+ * G: 70/200 = 35%
+ * R: 60/200 = 30%
+ * L: 38/200 = 19%
+ * H: 2/200 = 1%
+ * total (rounded) percentages = 85
+ */
+ int[] extracted = AAFrequency.extractProfile(profile, false);
+ int[] expected = new int[] { AlignmentAnnotation.SEQUENCE_PROFILE, 4,
+ 85, 'G', 35, 'R', 30, 'L', 19, 'H', 1 };
+ org.testng.Assert.assertEquals(extracted, expected);
+
+ /*
+ * add some counts of 1; these round down to 0% and should be discarded
+ */
+ counts.put('G', 68); // 68/200 = 34%
+ counts.put('Q', 1);
+ counts.put('K', 1);
+ extracted = AAFrequency.extractProfile(profile, false);
+ expected = new int[] { AlignmentAnnotation.SEQUENCE_PROFILE, 4, 84, 'G',
+ 34, 'R', 30, 'L', 19, 'H', 1 };
+ org.testng.Assert.assertEquals(extracted, expected);
+
+ }
+
+ @Test(groups = { "Functional" })
+ public void testExtractCdnaProfile()
+ {
+ /*
+ * 200 sequences of which 30 gapped (170 ungapped)
+ * max count 70 for modal residue 'G'
+ */
+ Hashtable profile = new Hashtable();
+
+ /*
+ * cdna profile is {seqCount, ungappedCount, codonCount1, ...codonCount64}
+ * where 1..64 positions correspond to encoded codons
+ * see CodingUtils.encodeCodon()
+ */
+ int[] codonCounts = new int[66];
+ char[] codon1 = new char[] { 'G', 'C', 'A' };
+ char[] codon2 = new char[] { 'c', 'C', 'A' };
+ char[] codon3 = new char[] { 't', 'g', 'A' };
+ char[] codon4 = new char[] { 'G', 'C', 't' };
+ int encoded1 = CodingUtils.encodeCodon(codon1);
+ int encoded2 = CodingUtils.encodeCodon(codon2);
+ int encoded3 = CodingUtils.encodeCodon(codon3);
+ int encoded4 = CodingUtils.encodeCodon(codon4);
+ codonCounts[2 + encoded1] = 30;
+ codonCounts[2 + encoded2] = 70;
+ codonCounts[2 + encoded3] = 9;
+ codonCounts[2 + encoded4] = 1;
+ codonCounts[0] = 120;
+ codonCounts[1] = 110;
+ profile.put(AAFrequency.PROFILE, codonCounts);
+
+ /*
+ * [0, noOfValues, totalPercent, char1, count1, ...]
+ * codon1: 30/110 = 27.2 = 27%
+ * codon2: 70/110 = 63.6% = 63%
+ * codon3: 9/110 = 8.1% = 8%
+ * codon4: 1/110 = 0.9% = 0% should be discarded
+ * total (rounded) percentages = 98
+ */
+ int[] extracted = AAFrequency.extractCdnaProfile(profile, true);
+ int[] expected = new int[] { AlignmentAnnotation.CDNA_PROFILE, 3, 98,
+ encoded2, 63, encoded1, 27, encoded3, 8 };
+ org.testng.Assert.assertEquals(extracted, expected);
+ }
+
+ @Test(groups = { "Functional" })
+ public void testExtractCdnaProfile_countGaps()
+ {
+ /*
+ * 200 sequences of which 30 gapped (170 ungapped)
+ * max count 70 for modal residue 'G'
+ */
+ Hashtable profile = new Hashtable();
+
+ /*
+ * cdna profile is {seqCount, ungappedCount, codonCount1, ...codonCount64}
+ * where 1..64 positions correspond to encoded codons
+ * see CodingUtils.encodeCodon()
+ */
+ int[] codonCounts = new int[66];
+ char[] codon1 = new char[] { 'G', 'C', 'A' };
+ char[] codon2 = new char[] { 'c', 'C', 'A' };
+ char[] codon3 = new char[] { 't', 'g', 'A' };
+ char[] codon4 = new char[] { 'G', 'C', 't' };
+ int encoded1 = CodingUtils.encodeCodon(codon1);
+ int encoded2 = CodingUtils.encodeCodon(codon2);
+ int encoded3 = CodingUtils.encodeCodon(codon3);
+ int encoded4 = CodingUtils.encodeCodon(codon4);
+ codonCounts[2 + encoded1] = 30;
+ codonCounts[2 + encoded2] = 70;
+ codonCounts[2 + encoded3] = 9;
+ codonCounts[2 + encoded4] = 1;
+ codonCounts[0] = 120;
+ codonCounts[1] = 110;
+ profile.put(AAFrequency.PROFILE, codonCounts);
+
+ /*
+ * [0, noOfValues, totalPercent, char1, count1, ...]
+ * codon1: 30/120 = 25%
+ * codon2: 70/120 = 58.3 = 58%
+ * codon3: 9/120 = 7.5 = 7%
+ * codon4: 1/120 = 0.8 = 0% should be discarded
+ * total (rounded) percentages = 90
+ */
+ int[] extracted = AAFrequency.extractCdnaProfile(profile, false);
+ int[] expected = new int[] { AlignmentAnnotation.CDNA_PROFILE, 3, 90,
+ encoded2, 58, encoded1, 25, encoded3, 7 };
+ org.testng.Assert.assertEquals(extracted, expected);
+ }
}