MULTIPLE ALIGNMENT ANALYSIS TOOLS

                USER INSTRUCTIONS                                







INTRODUCTION

This server will provide you with information about a possible functional and/or evolutionary two-way split in a protein family. All three programs take multiple sequence alignment of the family as the input. ANCESTRAL CENTERS program will, for each position without a gap, return a score. The smaller (i.e. more negative) the score, the more likely is this positon to contribute towards the split. CLUSTERING will divide your sequences into two groups with respect to the selected positions. Given a division of the protein family into two groups, REVERSE CLUSTERING will rank positions in the alignment according to their fitness with respect to this division.

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INPUT
All three programs take CLUSTAL alignments as input. If you have a CLUSTAL-like alignment - such as T-Coffee - please replace "T-Coffee" (or other) with "CLUSTAL". You can also submit a "left-justified" alignment, with names of the sequences submitted to the left hand window (names are optional). Sequences should contain only amino acids from the standard alphabet, with no "X". Please, replace "Xs" with some other letters, or, simply, remove the sequences containing "X" from the alignment. For the CLUSTERING program, you will have to select columns which will be used to obtain the clustering. You should select at least 2 valid columns (i.e. without a gap), and not more than 100. For REVERSE CLUSTERING, you have to give a division of your family into two groups. Neither of the groups should be empty.

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OUTPUT
ANCESTRAL CENTERS will return a table, where, for each position without the gap in the alignment, you get the hypothetical "ancestral amino acid=one center", the score of this model, two hypothetical "centers", the score of the two-center model, and the the difference of the scores. The smaller the number in the last column, the more likely is this position to be important for the split. CLUSTERING will return a table, with scores of each of the sequences with respect to two clusters, assignment to one of the clusters with respect to these scores, and  the absolute value of the difference of scores. REVERSE CLUSTERING will return a table, containing a score for each position without a gap in the alignment. The larger the score, the more likely is position significant for the proposed division.




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Department of Mathematics, University of Zagreb

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