* The alignment column on which the first profile is based.
* @param end
* The alignment column on which the last profile is based.
- * @param saveFullProfile
- * if true, all residue counts are saved (enables profile logo)
* @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 saveFullProfile,
- boolean removeBelowBackground, boolean infoLetterHeight)
+ int width, int start, int end, boolean removeBelowBackground,
+ boolean infoLetterHeight)
{
ProfileI[] result = new ProfileI[width];
char[] symbols = hmm.getSymbols().toCharArray();
int gapCount = counts.getGapCount();
ProfileI profile = new Profile(symbolCount, gapCount, maxCount,
maxResidue);
-
- if (saveFullProfile)
- {
- profile.setCounts(counts);
- }
+ profile.setCounts(counts);
result[column] = profile;
}
// hmm consensus sequence is shorter than the alignment
break;
}
- ProfileI profile = profiles.get(column);
- if (profile == null)
- {
- /*
- * happens if sequences calculated over were
- * shorter than alignment width
- */
- information.annotations[column] = null;
- return 0f;
- }
float value = hmm.getInformationContent(column);
boolean isNaN = Float.isNaN(value);
String description = isNaN ? null
: String.format("%.4f bits", value);
information.annotations[column] = new Annotation(
- Character.toString(Character
- .toUpperCase(hmm.getConsensusAtAlignColumn(column))),
+ Character.toString(
+ Character.toUpperCase(hmmSeq.getCharAt(column))),
description, ' ', value);
}
* @param endCol
* end column (exclusive)
*/
- public static void completeOccupancyAnnot(AlignmentAnnotation occupancy,
+ public static void completeGapAnnot(AlignmentAnnotation occupancy,
ProfilesI profiles, int startCol, int endCol, long nseq)
{
if (occupancy == null || occupancy.annotations == null