ACGTN

The name of the motif.

The alternate name of the motif.

The width of the motif. No gaps are allowed in motifs supplied to MAST as it only works for motifs of a fixed width.

The sequence that would achieve the best possible match score and its reverse complement for nucleotide motifs.

MAST computes the pairwise correlations between each pair of motifs. The correlation between two motifs is the maximum sum of Pearson's correlation coefficients for aligned columns divided by the width of the shorter motif. The maximum is found by trying all alignments of the two motifs.

Motifs with correlations below 0.60 have little effect on the accuracy of the E-values computed by MAST. Motifs with higher correlations with other motifs should be removed from the query. You can also request MAST to remove redundant motifs from its analysis under Advanced options from the MAST web page, or by specifying --remcorr when running MAST on your own computer.

The name of the (FASTA) sequence database file.

The number of sequences in the database.

The number of residues in the sequence database.

The date of the last modification to the sequence database.

The name of the file containing the (MEME-formatted) motifs used in the search.

The date of the last modification to the motif database.

This diagram shows the normal spacing of the motifs specified to MAST.

MAST will calculate larger p-values for sites that diverge from the order and spacing in the diagram.

The name of the sequence. This maybe be linked to search a sequence database for the sequence name.

The E-value of the sequence.

If strands were scored separately then there will be two E-values for the sequence separated by a slash (/). The score for the provided sequence will be first and the score for the reverse-complement will be second.

The block diagram shows the best non-overlapping tiling of motif matches on the sequence. These motif matches are the ones used by MAST to compute the E-value for the sequence. Hovering the mouse cursor over a motif match causes the display of the motif name, position p-value of the match and other details in the hovering text.

The description appearing after the identifier in the FASTA file used to specify the sequence.

The combined p-value of the sequence.

If strands were scored separately with a complementable alphabet then there will be two p-values for the sequence separated by a slash (/). The score for the given sequence will be first and the score for the reverse-complement will be second.

This indicates the offset used for translation of the DNA.

The annotated sequence shows a portion of the sequence with the matching motif sequences displayed above.

The displayed portion of the sequence can be modified by sliding the two buttons below the sequence block diagram so that the portion you want to see is between the two needles attached to the buttons. By default the two buttons move together but you can drag one individually by holding shift before you start the drag.

If the strands were scored separately then overlaps in motif sites may occur so you can choose to display only one strand at a time. This is done by selecting "Matches on given strand" or "Matches on opposite strand" from the drop-down list.

The name of the alphabet symbol.

The frequency of the alphabet symbol as defined by the background model.

The score for the match of a position in a sequence to a motif is computed by by summing the appropriate entry from each column of the position-dependent scoring matrix that represents the motif. Sequences shorter than one or more of the motifs are skipped.

The position p-value of a match is the probability of a single random subsequence of the length of the motif scoring at least as well as the observed match.

The sequence p-value of a score is defined as the probability of a random sequence of the same length containing some match with as good or better a score.

The combined p-value of a sequence measures the strength of the match of the sequence to all the motifs and is calculated by

  1. finding the score of the single best match of each motif to the sequence (best matches may overlap),
  2. calculating the sequence p-value of each score,
  3. forming the product of the p-values,
  4. taking the p-value of the product.

The E-value of a sequence is the expected number of sequences in a random database of the same size that would match the motifs as well as the sequence does and is equal to the combined p-value of the sequence times the number of sequences in the database.

Motif1
p-value8.23e-7
Start23
End33
Change the portion of annotated sequence by dragging the buttons; hold shift to drag them individually.
Sequence Comment:
Combined p-value:
/
Annotated Sequence

For further information on how to interpret these results or to get a copy of the MEME software please access http://meme-suite.org.

If you use MAST in your research, please cite the following paper:
Timothy L. Bailey and Michael Gribskov, "Combining evidence using p-values: application to sequence homology searches", Bioinformatics, 14(1):48-54, 1998. [pdf]

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Motifs

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Motifs with a pale red background are very similar to other earlier specified motifs and may be biasing the results.
It is recommended that you re-run MAST and request it to remove redundant motifs.

Motifs which are grayed-out were very similar to other earlier specified motifs and were removed from the scan as you requested.

Search Results

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Top Scoring Sequences

Inputs & Settings

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Alphabet

Sequences

The following sequence databases were supplied to MAST.

Database
Sequence Count
Residue Count
Last Modified

Motifs

The following motif databases were supplied to MAST.

Database
Last Modified

Nominal Order and Spacing

The expected order and spacing of the motifs (as specified by you).

Other Settings

Strand Handling
Max Correlation
Remove Correlated
Max Sequence E-value
Adjust Hit p-value
Displayed Hits
Displayed Weak Hits
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MAST version
(Release date: )
Reference
Timothy L. Bailey and Michael Gribskov, "Combining evidence using p-values: application to sequence homology searches", Bioinformatics, 14(1):48-54, 1998.
Command line summary
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