Difference between revisions of "Task 2 (MSUD)"
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=== Results === |
=== Results === |
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+ | The query sequences for the 4 subunits of BCKDC locate at /mnt/home/student/weish/master-practical-2013/task01/. |
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+ | Results for sequence search locate in the directory /mnt/home/student/weish/master-practical-2013/task02/01-seq-search/results. |
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+ | For BLAST and PSI-BLAST statistics (such as E-value, probability and identity) are stored in <nowiki>*.tsv</nowiki> files. |
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=== Discussion === |
=== Discussion === |
Revision as of 15:04, 4 May 2013
Contents
Sequence searches
Results
The query sequences for the 4 subunits of BCKDC locate at /mnt/home/student/weish/master-practical-2013/task01/.
Results for sequence search locate in the directory /mnt/home/student/weish/master-practical-2013/task02/01-seq-search/results. For BLAST and PSI-BLAST statistics (such as E-value, probability and identity) are stored in *.tsv files.
Discussion
Multiple sequence alignments
Results
The datsets can be found in /mnt/home/student/schillerl/MasterPractical/task2/datasets/
.
The MSAs are located at /mnt/home/student/schillerl/MasterPractical/task2/MSAs/
.
In the following sections the MSAs, visualised with Jalview, are shown.
BCKDHA
Low sequence identity
High sequence identity
Whole range sequence identity
BCKDHB
Low sequence identity
High sequence identity
Whole range sequence identity
DBT
Low sequence identity
High sequence identity
Whole range sequence identity
DLD
Low sequence identity
High sequence identity
Whole range sequence identity
Discussion
For the datasets with high sequence identity the three MSA programs Mafft, Muscle and T-Coffee come to similar results and find almost the same conserved blocks. Sometimes T-Coffee arranges gaps differently than the others and so does not find as much conserved columns. Especially at the ends of the sequences, the results of the programs differ a little. This is due to different scoring schemes that are used in the programs.
For low sequence identity, the programs have problems to find the right alignment. They don't agree in the position of gaps and also sometimes find different conserved columns. They don't cope with low similarity and so one can't really rely on these results.
For whole range sequence identity the results are similar w. r. t. many and different gaps at the ends of the sequences, but the programs agree more in the conserved columns that they find.
The results of Muscle and Mafft seem more similar to each other than to those of T-Coffee. T-Coffee often treats the ends of the sequences, which have low sequence identity, differently than the others.
Altogether, there appear regions with many conserved columns and those with many gaps. The conserved blocks or columns correspond to secondary structure elements and functionally important residues, respectively. Gaps in the alignment appear in regions where there are loops in the structure of the protein, so that insertions or deletions that occur during evolution don't alter the overall structure or function of the protein.
As criteria for a good alignment one could run different alignment algorithms like in this task and compare the results. If one of them finds more conserved columns, this might be better than another. Different programs can be better than others if different datasets are used, so it is always a good idea to try more than one algorithm and pick out the best result. Mafft is often a good choice because it generated relatively precise results but still is very fast.