Contents
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Zhang, M., Feng, R., Chen, X.,
Hu, B., and Zhang, H.
Feng, R., Leckman, J.F., and Zhang, H. (2004) Linkage Analysis of Ordinal Traits for Pedigree Data. Proc Natl Acad Sci. 101;16739-16744
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Any research using this program or the methods or ideas behind it should
acknowledge the use of LOT, and cite the references in the Citation section.
THIS SOFTWARE IS PROVIDED BY THE COLLABORATIVE
CENTER FOR STATISTICS IN SCIENCE AT YALE UNIVERSITY ¡°AS IS¡± AND ANY EXPRESS OR IMPLIED
WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
EVENT SHALL THE COLLABORATIVE CENTER FOR STATISTICS IN SCIENCE AT YALE
UNIVERSITY BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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I.
Data Input This part is modified from the Genehunter program to
accommodate the ordinal trait and to add the graphic user interface (GUI). See
Input file formats for the details.
II.
Inference of Inheritance Vectors This part is taken from the Genehunter program. The method
is described in (Kruglyak et al., 1996).
III.
Latent Variable Proportional-odds Logistic Model This step assesses a potential link between a marker and
the trait locus through the inheritance pattern at a locus. We use a
proportional-odds logistic model that includes two types of latent random
variables to detect association between a marker and a disease locus. The two
types of latent variables,
where x
is the vector of covariates that is available for each study subject,
IV.
Output This part uses JFreeChart library for GUI.
where |
Ascertainment
Sensitivity of Parameter Inputs
It is
important to assess the sensitivity of the
Input
file formats
The
input file for LOT uses a slightly modified format from supports input files the standard GENEHUNTER (or LINKAGE) format. Two
input files are required: a locus data file and pedigree file.
(I) locus file. This file contains information on genetic distances
between markers, number of alleles at each locus and their frequencies. We explain
this file using the sample.loc.
The first row of five numbers in sample.loc is
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31 0 0
5 0 |
31 is
the number of loci; also see LINKAGE manual.
0 refers
to risk locus; also see LINKAGE manual.
0 means
not sex linked; also see LINKAGE manual.
5 is the
designated program code used by LINKAGE, referring to MLINK.
0 is the
number of covariates. This is an added feature in
The second row of four numbers in sample.loc is
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0 0.0
0.0 0 |
The four numbers represent:
Mutation
locus:
= 0, if mutation rates are zero,
= the mutation locus number (input order) for
non-zero mutation rates.
Male
mutation rate.
Female
mutation rat
Linkage
disequilibrium
= 0, if loci
are assumed to be in linkage equilibrium.
= 1, if loci are in linkage disequilibrium. When loci are in linkage
equilibrium, allele frequencies must be given under each locus description;
otherwise, haplotype frequencies are provided.
The third row in sample.loc is
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1 2 3 4
5 ¡ 31 |
This gives the order of all marker loci, from D1S468 to
D1S1609.
The fourth row in sample.loc is
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1 2 |
1 refers
to the nature of the trait locus, and always use 1 for
2 means
that the trait locus is di-allelic
The fifth row in sample.loc is the assumed allele
frequencies of the trait locus.
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0.910000
0.090000 |
The sixth row in sample.loc is a single number, referring
to the number of liability
classes. Set it to 1 for
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1 |
The seventh row in sample.loc specifies the penetrances of
the genotypes at the diallelic trait locus.
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0.165000
0.575000 0.75000 |
The following rows specify the allele frequencies of each marker.
For example, marker D1S468 classified as type ¡°3¡± according to the LINKAGE program
terminology and has 9 alleles. Hence, we enter the following information.
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3 9 # D1S468 0.076492 0.014699 0.008799 0.261774
0.055894 0.026497 0.417558 0.132387 0.005899 |
The last marker is D1S1609.
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3 12 # D1S1609 0.005701 0.011301 0.073407 0.240124
0.330533 0.124312 0.096010 0.053705 0.050805 0.008501 0.002800 0.002800 |
After specifying all marker information, the following row is
included in the locus file to conform the format of the LINKAGE program,
but is not used by
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0 0 |
The
first 0 means no sex difference
The
second 0 means no interference
The next row in sample.loc specifies the recombination or map
distance between all markers
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0.000000 12.000000 13.710000 7.120000
8.280000 11.410000 15.850000 3.070000 13.830000 12.530000 7.020000
4.650000 11.820000 11.370000 3.510000 11.490000 12.210000 6.750000
4.780000 16.430000 10.140000 10.250000 6.020000 7.700000 7.220000
6.280000 7.570000 7.410000 12.870000 7.020000 |
Distances may be specified as either
recombination-fractions or centiMorgans, with the necessary assumption that if
EVERY distance is less than 0.5, they are all assumed to be
recombination-fractions, otherwise (if ANY distance is greater than 0.5) they
are interpreted as centiMorgan distances.
If one chooses to use a map distance, it should be in Kosambi cM.
The next row in sample.loc specifies the recombination or map
distance between all markers, and it is included in the locus file to conform
the format of the LINKAGE program, but is not used by
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1 0.1
0.45 |
The next row in sample.loc specifies in which order the phenotype
is coded.
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0 |
This row can either have a zero or a one. A zero here indicates
that lower numbers signify higher severity of the disease trait and higher
numbers signify lower severity. A one indicates that lower numbers signify
lower severity of the disease trait and higher numbers signify higher severity.
The last two rows in sample.loc specify the number of
levels and the threshold of each level if the phenotype were to be further
divided into levels.
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3 1 2 3 |
The ¡°3¡± on the first line in the example above indicates
that the phenotypes would be divided into 3 + 1 = 4 levels, namely 0, 1, 2 and
3. The next line provides the threshold for each level. A phenotype is assigned
level 0 if it is strictly smaller than the first threshold, which is ¡°1¡± in the
example. A phenotype is assigned level 1 if it is larger or equal to 1 and
strictly smaller than 2. A phenotype is assigned level 2 if it is larger or
equal to 2 and strictly smaller than 3. If a phenotype is larger or equal to 3,
then it is assigned level 3. In this sense, the threshold for the level 3 (the
highest level) is positive infinity and hence omitted. Thus, only 3 thresholds
are provided for 4 levels. The assignment of phenotype Y in the above example can be summarized in the following table.
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Phenotype Y |
Level |
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0 |
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1 |
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2 |
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3 |
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999 |
(II) Pedigree file. This file must consist of columns with the following
information in the correct order (e.g., sample.ped):
Pedigree_ID
Person_ID Father_ID Mother_ID Gender Phenotype Marker_genotypes Covariates.
The columns should be separated by spaces or tabs (any
number of these is allowed).
1) Pedigree
ID: pedigree identifier
2) Person
ID: individual identifier
3) Father
ID and Mother ID: founders¡¯ parents are coded as 0. Note: Everyone must have
either two parents or no parents in the data set. Enter 0 if one or both
parents are not available.
4) Gender
and, for the gender column (1 = Male and 2 = Female). Note that gender can be
re-entered again as duplicated column later to serve as a covariate.
5) Phenotype(Y):
Missing phenotypes can be coded as 999.
6) Marker
genotype code: to code a codominant marker locus phenotype, simply list the two
numbered alleles with at least one space or tab between the alleles. The
unknown genotype is coded as 0 0.
7) The
covariates such as gender and age.
The pedigree/person IDs are treated as character strings.
They do not have to be integers or numbered sequentially. The phenotype and
covariates can be integers or reals.
Downloads
Executables
LOT_Windows.exe: Self-extracting
archive for installation on Windows system.
LOT_Windows_command_line.exe: executable file
for evoking
LOT_Linux.tar.gz: GZIP-compressed Tar file containing
executable on Linux system. (The javax.swing package is
required to be installed in your system before running
LOT_Linux_command_line: executable
file for evoking
LOT_Mac_command_line: executable file for evoking
Sample Files
sample.loc: Sample locus file.
sample.ped: Sample pedigree
file.
sample.ped.output: Sample output
file.
sample.png: Sample output
file.
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Running
a.
Running
The user also has the option to suppress the marker names displayed on the curve by clicking on the ¡°Hide Significant Markers¡± button on the lower left corner of the window.
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b.
Running
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After downloading LOT_Windows_command_line.exe there are two options to evoke it.
Double click on
LOT_Windows_command_line.exe and a DOS window will pop up. The user will be
prompted to enter the .ped, .loc and output file names. After the file names
are provided, the
In the folder where
LOT_Windows_command_line.exe is saved, it can be evoked by typing
¡°LOT_Windows_command_line.exe sample.ped sample.loc sample_output.txt¡± in a DOS
window. Replace ¡°sample.ped¡±, ¡°sample.loc¡± and ¡°sample_output.txt¡± with the
name of the pedigree file, locus file and output file of your choices. If more
or less than three file names were provided, the program would prompt the user
to enter the file names again.
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Please note that if the
files are not located in the same folder as the executable, use the full path
instead of just the file names. The tab-delimited text output is the only
output file provided under this option. |
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c.
Running After downloading LOT_Linux_command_line,
in the folder where LOT_Linux_command_line
is saved, it can be evoked by typing ¡°./LOT_Linux_command_line sample.ped sample.loc sample_output.txt¡± in a terminal
window. Replace ¡°sample.ped¡±, ¡°sample.loc¡± and ¡°sample_output.txt¡± with the
name of the pedigree file, locus file and output file of your choices. If
more or less than three file names were provided, the program would prompt
the user to enter the file names again. Please note that if the
files are not located in the same folder as the executable, use the full path
instead of just the file names. If white
spaces are part of a file name (or path), enclose the file name (or the path)
with ¡°¡±. The tab-delimited text output is
the only output file provided under this option. |
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d.
Running LOT from command line in Mac OS X. After downloading LOT_Mac_command_line,
in the folder where LOT_Mac_command_line
is saved, it can be evoked by typing ¡°./LOT_Mac_command_line sample.ped sample.loc sample_output.txt¡± in a terminal
window. Replace ¡°sample.ped¡±, ¡°sample.loc¡± and ¡°sample_output.txt¡± with the
name of the pedigree file, locus file and output file of your choices. If
more or less than three file names were provided, the program would prompt
the user to enter the file names again. Please note that if the
files are not located in the same folder as the executable, use the full path
instead of just the file names. If white
spaces are part of a file name (or path), enclose the file name (or the path)
with ¡°¡±. The tab-delimited text output is
the only output file provided under this option. |
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Below is the GENEHUNTER license agreement listed as required by GENEHUNTER.
* License
Agreement
Copyright
(c) 1995
Whitehead Institute for Biomedical Research. All rights reserved.
Redistribution
and use in source and binary forms, with or without
modification,
are permitted provided that the following conditions are met:
1. Redistributions
must reproduce the above copyright notice, this
list of
conditions and the following disclaimer in the documentation
and/or
other materials provided with the distribution. Redistributions of
source
code must also reproduce this information in the source code itself.
2. If the program
is modified, redistributions must include a notice
(in the
same places as above) indicating that the redistributed program is
not
identical to the version distributed by Whitehead Institute.
3. All advertising
materials mentioning features or use of this
software must display the following
acknowledgement:
This
product includes software developed by the
Whitehead Institute for Biomedical Research.
4. The name of the
Whitehead Institute may not be used to endorse or
promote
products derived from this software
without specific prior written
permission.
We request
that users of this software inform us by sending email to
software_registration@genome.wi.mit.edu.
We also request
that use of this software be cited in publications as:
L.
Kruglyak, M.J. Daly, M.P. Reeve-Daly, and E.S. Lander. "Parametric
and
Nonparametric Linkage Analysis: A Unified
American
Journal of Human Genetics 58:1347-1363 (June 1996). For
versions
1.2 and above, please also cite: L. Kruglyak and
E.S.
Lander. "Faster
Transforms". Journal of Computational Biology 5:1-7
(1998).
THIS
SOFTWARE IS PROVIDED BY THE WHITEHEAD INSTITUTE ``AS IS'' AND ANY
EXPRESS OR
IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES
OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED.
IN NO EVENT SHALL THE WHITEHEAD INSTITUTE BE LIABLE FOR ANY
DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING,
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
OUT OF THE
USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
SUCH
DAMAGE.