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<!-- header fragment for html documentation -->
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<META NAME="description" CONTENT="Estimation of population parameters using genetic data usi
ng a maximum likelihood approach with Metropolis-Hastings Monte Carlo Markov chain importanc
e sampling">
<META NAME="keywords" CONTENT="MCMC, Markov chain, Monte Carlo, Metropolis-Hastings, populat
ion, parameters, migration rate, population size, recombination rate, maximum likelihood">
<TITLE>LAMARC Documentation:
Modeling Linkage Properties and Relative Mutation Rates of Your Data</title>
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<!-- coalescent, coalescence, Markov chain Monte Carlo simulation, migration rate, effective
population size, recombination rate, maximum likelihood -->
<P>(<A HREF="converter.html">Back</A> | <A HREF="index.html">Contents</A>
| <A HREF="migration_matrix.html">Next</A>)</P>
<h2>Modeling Linkage Properties and Relative Mutation Rates of Your Data</h2>
<p>
<em>(Note: it is recommended that you be familiar with the material
in the <a href="converter.html">data file conversion</a>
section before reading this section.)</em>
</p>
<p>
LAMARC is a coalescent analysis program.
It constructs and analyzes many different possible genealogies
(trees) representing the common ancestor relationships among the
data sequences sampled. You will need to guide LAMARC's search by
specifying how samples from different portions of your organism's
genome are related.
For example,
<ul>
<li>
data from different chromosomes (or from sufficiently
distant portions of the same chromosome)
should be modeled with independent genealogies, and
</li>
<li>
samples with known differences in relative mutation rate (such as
introns and exons within a single sequence)
should be subdivided into portions corresponding to those
different mutation rates.
</li>
</ul>
</p>
<p>
In order to guide LAMARC's search through appropriate
genealogies, you will need to be able to partition your data samples into
<ul>
<li><a href="#coherent-segment">coherent segments</a> (closely linked data )
<li><a href="#region-coord">linked segment regions</a> (loosely linked
data), and
<li>populations (groups of inter-breeding individuals).
</ul>
</p>
<P> Modeling these different properties
will allow you to do an analysis with multiple chromosomal regions and/or
multiple populations. You can combine several files together into a
single LAMARC input file. These input files do not need to be in the same
file format, as long as they are all files the converter can read (i.e. you
can stick together two PHYLIP files and a MIGRATE file into a single LAMARC
dataset).</P>
<P>Older versions of LAMARC only allowed one to mix different data types
only when they were unlinked from each other (i.e. in different linked
segment regions).
As of LAMARC 2.1, we have relaxed even this restriction, allowing you to
mix and match different data types even when they are linked. So, for
example, the increasingly-popular data type of
<a href="#microsat-snp">microsatellite next to a SNP</a>
may now be modeled in LAMARC and will be analyzed appropriately.</P>
<h3><a name="coherent-segment">Coherent Segments</a></h3>
<p>
A coherent segment (or 'segment' for short) is:
<ul>
<li>one or more genetic markers, </li>
<li>all of the same data type, </li>
<li>arranged in sequence order as on the genome, </li>
<li>with (almost) no missing or omitted data, and </li>
<li>(in most cases) having similar mutation rates. </li>
</ul>
</p>
<h4>Missing Data</h4>
<p>
Note that "missing data" is defined differently for different
data types. For example, SNPs
come as markers and a series
of spacings.
However, a set of SNPs count as a 'coherent segment' --
while we don't know what the sequence is between the
SNPs, we do know that it doesn't vary.
Linked microsatellite data is similar -- the number of microsat
repeats and their relative locations are relevant, not the sequences
between them.
</p>
<p>
Occasional missing or corrupted data is represented in the input
files with a "<tt>?</tt>" character.
</p>
<h4>Similar Mutation Rates</h4>
<P>
LAMARC's default assumption is that sampled locations within a single
segment have the same mutation rate. This assumption can be changed
with the <a href="data_models.html#rateCategories">rate categories</a>
feature in the lamarc menu. However, that feature has LAMARC identify
different mutation rates for each site.</p>
<p>
When you have sections within a stretch of sampled data for which you know
that the mutation rates differ, it may be more appropriate to model them as
different coherent segments within the same linked segment region.
For example, if you have sequenced a gene with multiple
introns and exons, you can include each intron and exon as a coherent
segment, each with an appropriate relative mutation rate, and then combine
them all into a single linked segement region.</P>
<!---LS NOTE: if we test and provide a
way to allow 'wobble base' overlapped segments, we can talk about this here.
It would probably work with an unmodified 2.1, but we should test it
first.-->
<p>
<em>
Note:
As of LAMARC 2.1,
<a href="data_models.html">relative mutation rates</a>
can only be set from the
<a href="menu.html#data">data model menu</a>
of the lamarc program.
If you wish to model introns and exons with separate relative
mutation rates, place them in separate coherent segments
during the conversion process, and set the relative mutation
rates from the lamarc program itself.
A more complete discussion of the many ways you can accomodate
data with different mutation rates is found in section
<a href="gamma.html">Combining Data with Different Mutation Rates</a>.
</em>
</p>
<h4><a name="segment-coord">Length and Spacing Information with
Segment Coordinates</a></h4>
<p>
Below is a screen shot from the lamarc converter showing the
detail panel for coherent segment <tt>chrom2-segment1</tt> that
results when <a href="converter_cmd.html">command file</a>
<a href="batch_converter/sample-conv-cmd.html">sample-conv-cmd.xml</a>
(actual xml is <a href="batch_converter/sample-conv-cmd.xml">here</a>)
is read into the lamarc converter.
</p>
<img src="batch_converter/images/lam_conv_chrom2_segment1.png" alt="xxx"/>
<p>
The second column from the left displays the following quantities,
which together specify the relative spacing of data within a segment.
<ul>
<li><em>Number of Markers</em> -- the number of sites with data. For
DNA it is the number of sites sequences; for SNPs it is the number
of SNPs; for Kallele and Microsattelite data it is the number of
distinct sites at which kallele/msat data was found</li>
<li><em>Total Length</em> -- total number of bases searched for data</li>
<li><em>First Position Scanned</em> --
the location of the first sampled location in your data
</li>
<li><em>Locations of sampled markers</em> --
the location of each particular marker of your data, in the same
coordinates as the first position scanned.
</li>
</ul>
</p>
<p>
The last two of these quantities are measured in
"segment coordinates": they are local to the appropriate
segment. Thus, if your first position scanned is -5 and your first
location is 2, your first SNP is the 7th position scanned.
<em>
(If you're wondering why it isn't the 8th position, see question
<A HREF="troubleshooting.html#Q14">Does LAMARC use 'site 0'? Do I?</a>.)
</em>
</p>
<p>
See also <a href="#region-coord">Region Coordinates.</a>
</p>
<h3><a name="region-coord">Linked Segment Regions and Region Coordinates</a></h3>
<P>Once your data is divided up into coherent segments, if any of these are
genetically linked to one another, you can combine them into a linked
segment region (or 'region' for short). Unrelated coherent segments
each belong in their own region.
</p>
<p>
The Segment Panel pictured above for <tt>chrom2-segment1</tt>
displays a <tt>Map Position</tt> of <tt>1000</tt>.
Whenever you have more than one coherent segment in a region, you
will need to know their relative spacing. This is entered as the
"map position" and is required to:
<ul>
<li>verify that the segments are non-overlapping, and</li>
<li>model intervening recombinations correctly.</li>
</ul>
</p>
<p>
All Map Positions are given using a single coordinate
system for the region, the "regional coordinates"
system.
If you wish to use region-wide coordinates within segments as
well, you may. Your <tt>first position scanned</tt> would be
identical to your <tt>map position</tt> and all <tt>location</tt>
values should have values between your <tt>map position</tt>
value and the <tt>map position</tt> plus the <tt>length</tt>.
</p>
<P> Do not put samples together in a region if you have reason to
believe they are actually unlinked.
This will result in wrong answers.
If you put unlinked markers together in a region and also estimate
recombination, you will get wrong answers and the program will bog down
horribly as it tries to estimate an infinite recombination rate.
</P>
<p>
The total length of genome that can
be included in a single region when estimating recombination has an upper
limit of about a centimorgan, though an extensive study with many samples of
that length might bog down LAMARC considerably and run very slowly. A more
reasonable length is probably half of that. As a quick rule of thumb, we've
found that LAMARC runs smoothly for runs where Theta times the recombination
rate times the total length of a region is 10 or less.</P>
<h3><a name="microsat-snp">A Multi-Segment Example: Microsatellite next to SNP</a></h3>
<P>If you have data with a microsatellite next to a SNP, you
want the microsatellite as one coherent segment, the SNP as another coherent
segment, and both segments as part of the same linked segment region.
This section of the documentation walks you through creating such a
file with the converter in GUI mode.
</P>
<p>
Below is a picture of the converter after you have read in the files
<a href="batch_converter/chrom3microsat.mig">chrom3microsat.mig</a> and
<a href="batch_converter/chrom3snp.mig">chrom3snp.mig</a>, and have
set the data types appropriately.
</p>
<img src="batch_converter/images/lam_conv_chrom3_input.png" alt="xxx"/>
<p>
Since we are modeling an adjacent microsat and SNP, we need to place
them in the same region. Otherwise, LAMARC will analyze them separatedly.
To do this, double click the text inside either of the boxes
labeled <tt>region</tt> within the <tt>Data Partitions</tt>.
</p>
<p>
You'll see a panel similar to this:
</p>
<img src="batch_converter/images/lam_conv_chrom3_region_panel.png" alt="xxx"/>
<p>
Select the single box within the <tt>Merge with selected Region</tt>
area and click <tt>Apply</tt>. When you return to the main GUI window,
you will notice that the two coherent segments are now included in
one region like this:
</p>
<img src="batch_converter/images/lam_conv_chrom3_region_table.png" alt="xxx"/>
<p>
Unfortunately the two data files name their samples in different ways:
the SNP file names each haploid sample while the Microsattelite data
names each individual. If you try to write a lamarc file at this point,
you will get this error:
</p>
<img src="batch_converter/images/lam_conv_chrom3_error_phase_file_needed.png" alt="xxx"/>
<p>
The solution is to write a
<a href="converter_cmd.html#phase">phase information file</a>
like this:
</p>
<pre>
<lamarc-converter-cmd>
<individuals>
<individual>
<name>n_ind0</name>
<sample><name>n_ind0_a</name></sample>
<sample><name>n_ind0_b</name></sample>
</individual>
<individual>
<name>n_ind1</name>
<sample><name>n_ind1_a</name></sample>
<sample><name>n_ind1_b</name></sample>
</individual>
<individual>
<name>n_ind2</name>
<sample><name>n_ind2_a</name></sample>
<sample><name>n_ind2_b</name></sample>
</individual>
<individual>
<name>s_ind0</name>
<sample><name>s_ind0_a</name></sample>
<sample><name>s_ind0_b</name></sample>
</individual>
<individual>
<name>s_ind1</name>
<sample><name>s_ind1_a</name></sample>
<sample><name>s_ind1_b</name></sample>
</individual>
</individuals>
</lamarc-converter-cmd>
</pre>
<p>
You can also find the actual xml
<a href="batch_converter/chrom3_phase_cmd.xml">chrom3_phase_cmd.xml</a> here
<br>Read it in using the menu commands <tt>File > Read Command File</tt>.
</p>
<p>
Alas, we are still not ready to write a Lamarc file. Attempting to do so results
in this error:
</p>
<img src="batch_converter/images/lam_conv_chrom3_error_map_position.png" alt="xxx"/>
<p>
The problem is that we don't know how close together the microsatellite and
the SNP are. To solve this problem you'll need to edit fields on the
segment panels for each coherent segment.
</p>
<p>
Begin by setting the map position of the microsatelite segment to 500.
Then edit the snp segment as shown here.
</p>
<img src="batch_converter/images/lam_conv_chrom3_segment_snp.png" alt="xxx"/>
<p>
<ul>
<li> map position -- 501 -- in global co-ordinates, the location of the
start of the area scanned for SNPs,
<li> total length -- 100 -- the total length scanned for SNPS
<li> first postion scanned -- 1 -- establishes a
<li> locations of sampled markers -- 23 -- in the segment coordinates, where the
SNP was found
</ul>
You should now be able to write the Lamarc file.
</p>
<P>(<A HREF="converter.html">Back</A> | <A HREF="index.html">Contents</A>
| <A HREF="migration_matrix.html">Next</A>)</P>
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