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Only the visual basic scripts are currently limited to Window operating systems (OS) since other OSs do not use the same
objects (for example OS9 for Macintosh), but there is no overt support of any
company or product. If there is significant in re-writing the package
into another format please contact Kenneth Berendzen at
@
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Usage Introduction
Motif Mapper is a tool for frequency analysis. Frequency analysis is
the study of how often a particular motif occurs in a specific sequence set.
In other words, you can ask and answer these questions :
Motif Mapper handles multiple data sets against a lists of motif queries. The
limit of the number of files and the number of queries is up to you. This approach
allows one to screen different sequence sets with the same group of motifs.
There are two output files, one for each motif and sequence and a summary file
which considers the entire data set together as one. The frequency output
from Motif Mapper is precise and can be used to compare different sets effectively.
By comparing different sequence sets, you establish a biological statistic instead of
relying on a mathematical approximation.
Since long lists of motifs can be used to query sequence sets one can think about
conducting mutation or permutation analysis. For example, you have a motif and would like to
know what is the probability of there being an "A" at the 5' flank compared
to the other three nucleotides you could enter four motifs with each of the
four DNA nucleotides at the 5' end and check to see. Motif Mapper comes with some computational
tools for conducting permutation/mutation analysis under the MotifList_Generator Module.
Defining motifs
Identifying motifs is not an easy task. Often information is lacking and
only very well characterized elements can be trusted
to be functional. If you have a set of promoters that you feel should be co-regulated
one can try MEME,
but we highly recommend the pattern discovery programs from
Regulatory Sequence Analysis Tools (RSAT).
RSAT is the most sophisticated frequency based analysis tool available.
If you work with plants, then you might want to examine the cis-element databases that
are routinely maintained; PLACE is
an excellent source as is PlantCARE.
Other cis-element sources can be found under External Links from
TAIR.
Establishing significance
1. Trust the significance values provided by the programs you used to identify motifs.
It is up to you to read up on everything you can find explaining what the statistics mean.
2. Consider known biological information, does it make sense as to what type of motifs have been discovered?
Is there an element that is missing that you know has a conserved function in at least
some of the promoters you are analyzing? Are your search criteria too stringent or have you
excluded DNA regions that may contain the elements you are looking for?
If so, go back and repeat with either less stringent screening parameters or maybe you
should take more flanking sequence and annotate by hand.
MMfasta and MMGraphicP allows you to
map elements from FASTA formatted sequences.
Example output from MMfasta is included in the Getting Started page.
3. For elements that are quite frequent, then you might consider making
frequency-distribution curves with IUPAC words or a Position Point Matrix,
or looking for linked motifs by indulging dyad analysis.
Or, you might also want to experiment with mutation analysis to see what
changes occur in the curve shape.
4. Establish your own statistic with assistance from Motif Mapper.
Final Word
Motif Mapper was created to be modular, simple and as flexible as possible so that the
effectiveness is dependent on what questions you ask and how you go about answering them.
Give yourself time to get used to the package setup. If there are any suggestions,
questions, comments or contributions please contact us.
Suggested data sets
The advantage to learning Motif Mapper.
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