GENEHUNTER-IMPRINTING
GENEHUNTER-IMPRINTING is a modification of the
GENEHUNTER software package
(versions 1.3 and 2.1 release 3; Kruglyak et al. 1996;
Kruglyak and Lander 1998; Markianos et al. 2001). It allows for a
parametric multi-marker linkage analysis of dichotomous traits
caused by imprinted genes – that is, of traits showing a
parent-of-origin effect. By specification of two heterozygote
penetrance parameters, paternal and maternal origin of the disease
allele can be treated differently in terms of probability of
expression of the trait. Therefore, a disease model which accounts
for imprinting includes four penetrances instead of only three.
For an analysis with a four-penetrance imprinting model, the
command 'imprinting on' needs to be entered at the beginning of a
GENEHUNTER-IMPRINTING session. Otherwise, LOD scores are
calculated under a standard three-penetrance model, in the same
way as with the original GENEHUNTER.
The imprinting extension does not affect NPL-score calculation or
other types of analysis available with GENEHUNTER version 2
(affected sib pair, QTL, and TDT analyses).
More information about GENEHUNTER-IMPRINTING can be found in the
file INSTALL.ghi that is included in the archives provided below.
Please also see the on-line help for details, e.g. by typing 'help
load markers' or 'help imprinting' at the GHI prompt, or refer to
the PostScript version of the online help (file ghi.ps).
Reference publication for GENEHUNTER-IMPRINTING
Strauch K, Fimmers R, Kurz T, Deichmann KA, Wienker TF,
Baur MP (2000):
Parametric and nonparametric multipoint linkage analysis with imprinting
and two-locus-trait models: application to mite sensitization.
American Journal of Human Genetics 66:1945-1957.
Download
Please note that the latest program extension
GENEHUNTER-MODSCORE
(please see below) offers all of the functionality of
GENEHUNTER-IMPRINTING and also includes further methodological and
algorithmic improvements. It is, however, still useful to employ
GENEHUNTER-IMPRINTING version 1.3 if X-chromosomal loci should be
analyzed, since GENEHUNTER-MODSCORE can only handle (pseudo)autosomal
loci.
Version 1.3 allows for an analysis of autosomal as well as
X-chromosomal loci – unlike the later versions that can only
analyze autosomal loci. Hence, for an analysis of the X
chromosome, version 1.3 should be used.
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GENEHUNTER-IMPRINTING version 2.1 release 3:
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Installation instructions and copyright notice:
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INSTALL.ghi-2.1 /
COPYRIGHT.ghi-2.1
(included in the download packages)
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Command reference (on-line help texts):
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ghi-2.1.pdf
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Version 2.1 release 3 is mentioned here for completeness; all of its
functionality is also available in GENEHUNTER-MODSCORE that includes
further improvements, as described below.
GENEHUNTER-MODSCORE
NEW: Version 3.0 calculates P values
for MOD and LOD scores by performing simulations
As of version 2.0, the program allows for
sex-specific recombination fractions
and automatically reads genetic maps
GENEHUNTER-MODSCORE is a further extension of
GENEHUNTER-IMPRINTING
(as described above). The program is based on the original
GENEHUNTER
version 2.1 release 6 (Kruglyak et al. 1996; Kruglyak and
Lander 1998; Markianos et al. 2001); it can handle autosomal or
pseudoautosomal loci. GENEHUNTER-MODSCORE allows
for a MOD-score analysis, in which parametric LOD scores are maximized
over the parameters of the trait model, i.e., the penetrances and
disease allele frequency. By this means, the disease-model
parameter space is explored in an efficient way, and so researchers
do not have to rely on a single trait model when performing a
parametric linkage analysis. This can be of great help in the
context of genetically complex traits, for which the disease model
parameters are usually unknown prior to the analysis. Please note
that, because of the additional maximization, MOD scores are
inflated when compared to LOD scores that were calculated under
a single trait model. Therefore, in the context of a MOD-score
analysis, significance criteria for LOD scores cannot be applied
without correction. For details regarding this issue, please see the
references (Strauch et al. 2000; 2005) mentioned below.
In order to address this issue, a simulation routine has been
introduced with version 3.0, in conjunction with a wider range of
maximization options. This allows users to calculate empirical
P values for MOD scores and simple LOD scores. Hence,
significance criteria can also be applied in a MOD-score analysis.
Please refer to the article by Mattheisen et al. ("Inferential testing
for linkage with GENEHUNTER-MODSCORE: the impact of the pedigree
structure on the null distribution of multipoint MOD scores",
Genetic Epidemiology 32:73-83, 2008)
for details. By performing simulations under various scenarios, it is
shown that, under the null hypothesis of no linkage, the inflation of
MOD scores with respect to simple LOD scores increases with the size of
pedigrees in the sample. This issue has also been discussed
theoretically by Strauch ("MOD-score analysis with simple pedigrees:
an overview of likelihood-based linkage methods",
Human Heredity 64:192-202, 2007).
The core of GENEHUNTER-MODSCORE is a highly optimized engine for
the calculation of the disease-locus likelihood. Here, the same
techniques were used as for the optimization of the program
GENEHUNTER-TWOLOCUS
(Dietter et al., "Efficient two-trait-locus
linkage analysis through program optimization and parallelization:
application to hypercholesterolemia",
European Journal of Human Genetics 12:542-550, 2004;
please see also below). With GENEHUNTER-MODSCORE, the optimizations
have led to a speed-up of a factor of almost 6. This is already of
benefit in a standard LOD-score analysis, but it is absolutely
essential for a maximization over models, which is much more
demanding.
As of version 2.0, GENEHUNTER-MODSCORE allows researchers to use
sex-specific recombination frequencies. In accordance with that,
the program employs an intuitive and consistent method to choose the
combinations of male and female genetic distances between the
disease locus and its flanking markers at which the LOD, MOD, or NPL
scores should be calculated. Please refer to the article by
Dietter et al. ("Linkage analysis using sex-specific recombination
fractions with GENEHUNTER-MODSCORE",
Bioinformatics 23:64-70, 2007)
for a detailed description of this method. The genetic positions of
markers can be automatically read from a publicly available genetic
map, such as the deCODE, Duffy, Marshfield, Nievergelt-Schork, or
the Rutgers map. The option to use sex-specific recombination
fractions also extends to the affected-sib-pair and QTL analysis
capabilities of GENEHUNTER.
A Perl script, GH_modview (written by Franz Rüschendorf,
e-mail:
fruesch@mdc-berlin.de),
is provided with GENEHUNTER-MODSCORE. It allows for the creation
of a Gnuplot graph of the
LOD or MOD score, displayed by the single family contributions. An
example of such a plot obtained for a sample with three pedigrees is
shown below. Each familiy is represented by a different color.
For every genetic position, the contribution of a family that yields a
score above zero is added to the positive side of the y-axis, and the
contribution of a family that yields a score below zero is added to
the negative side of the y-axis. The overall score at a genetic
position equals the total positive score (i.e., the sum over all
families with positive contribution) minus the total negative score.
This type of diagram is useful for both Mendelian and complex traits,
since it identifies families with positive versus negative contribution
to the linkage signal at a particular genetic position.
GENEHUNTER-MODSCORE can perform separate maximizations over penetrances
of several liability classes, e.g. for males and females, individuals
of different age, or different levels of risk due to environmental
factors. By this means, it is also possible to study gene-environment
interactions.
In case that a genome scan for a certain trait yields at least two
linkage peaks, it is reasonable to perform a linkage analysis that
explicitly models two trait loci. Such an analysis can be done with
the program GENEHUNTER-TWOLOCUS.
In the parametric context, the best-fitting trait models at the two
loci obtained by a MOD-score analysis with GENEHUNTER-MODSCORE can be
used to derive the underlying two-locus trait model. Please see
below for details regarding this
issue.
More information about GENEHUNTER-MODSCORE can be found in the file
INSTALL.ghm that is included in the
archives provided below.
Please also see the on-line help for details, e.g. by typing 'help
modcalc' or 'help modscore' at the GHM prompt, or refer to the PDF
or PostScript version of the online help
(files ghm.pdf and ghm.ps,
respectively).
Reference publications for GENEHUNTER-MODSCORE
Mattheisen M, Dietter J, Knapp M, Baur MP, Strauch K (2008):
Inferential testing for linkage with GENEHUNTER-MODSCORE: the impact
of the pedigree structure on the null distribution of multipoint MOD
scores.
Genetic Epidemiology 32:73-83.
Dietter J, Mattheisen M, Fürst R, Rüschendorf F, Wienker TF,
Strauch K (2007):
Linkage analysis using sex-specific recombination fractions with
GENEHUNTER-MODSCORE.
Bioinformatics 23:64-70.
Strauch K, Fürst R, Rüschendorf F, Windemuth C,
Dietter J, Flaquer A, Baur MP, Wienker TF (2005):
Linkage analysis of alcohol dependence using MOD scores.
BMC
Genetics 6(Suppl1):S162.
Strauch K (2003):
Parametric linkage analysis with automatic optimization of the
disease model parameters.
American Journal of Human Genetics 73(Suppl1):A2624.
Reference publication for the imprinting analysis option
Strauch K, Fimmers R, Kurz T, Deichmann KA, Wienker TF,
Baur MP (2000):
Parametric and nonparametric multipoint linkage analysis with imprinting
and two-locus-trait models: application to mite sensitization.
American Journal of Human Genetics 66:1945-1957.
Download
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GENEHUNTER-MODSCORE version 3.0:
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Installation instructions and copyright notice:
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INSTALL.ghm-3.0 /
COPYRIGHT.ghm-3.0
(included in the download packages)
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Command reference (on-line help texts):
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ghm-3.0.pdf
(included in the download packages)
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The author of the simulation routine and the additional maximization
options is Manuel Mattheisen (mmattheisen@uni-bonn.de).
The author of the functionality to use sex-specific recombination
frequencies, including the handling of maps, is
Johannes Dietter.
The archives contain sample input files for a MOD-score analysis
(sample.in and
sample_use_map.in),
in conjunction with the files linkloci.dat,
linkloci.dat.sxp,
linkloci.imp,
linkloci.imp.sxp, and
linkped.pre.
Furthermore, map files with the genetic positions of markers
according to the Duffy, Marshfield, Nievergelt-Schork, and the
Rutgers map are included (with kind permission by David Duffy,
Karl Broman, Nicholas Schork, and Tara Matise). A sample run can
be executed e.g. by typing 'run sample_use_map.in' at the GHM
prompt, or by calling 'ghm < sample_use_map.in' from the
command shell.
Under MS-Windows, you may need to add a file
gnuplot.bat (that calls wgnuplot.exe)
to the Gnuplot\bin subdirectory so that the 'gnuplot' command,
executed by GH_modview, works properly. This subdirectory should
also be included in the Path environment variable.
Previous versions
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GENEHUNTER-MODSCORE version 2.0.1 (old):
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Installation instructions and copyright notice:
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INSTALL.ghm-2.0.1 /
COPYRIGHT.ghm-2.0.1
(included in the download packages)
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Command reference (on-line help texts):
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ghm-2.0.1.pdf
(included in the download packages)
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As of version 2.0, GENEHUNTER-MODSCORE can handle sex-specific
recombination frequencies and automatically read genetic maps.
A bug occurred with version 2.0 if the analyzed genetic positions
reached beyond the end of a chromosome as defined in the genetic map
file, or with only one marker when no genetic map file was used.
This has been fixed in version 2.0.1.
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GENEHUNTER-MODSCORE version 1.1 (old):
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Installation instructions and copyright notice:
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INSTALL.ghm-1.1 /
COPYRIGHT.ghm-1.1
(included in the download packages)
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Command reference (on-line help texts):
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ghm-1.1.pdf
(included in the download packages)
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With GENEHUNTER-MODSCORE 1.1, the restriction of the disease allele
frequency in a MOD-score analysis ('allfreq restriction' command) has
been changed so that the user can specify the highest bound ('highest
allfreq' command). The default is 'highest allfreq 0.5'. It is also
possible to perform a MOD-score analysis without any restriction on the
disease allele frequency by specifying 'allfreq restriction off'.
Please also see the help texts for the 'allfreq restriction' and
'highest allfreq' commands. In addition, it is now possible to turn
'imprinting' from 'off' to 'on' (but, for technical reasons, not vice
versa) within the same run of the program. This allows researchers to
perform a MOD-score analysis without imprinting, directly followed by a
second MOD-score round that takes imprinting into account, without
having to restart the program.
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GENEHUNTER-MODSCORE version 1.0 (old):
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Installation instructions and copyright notice:
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INSTALL.ghm-1.0 /
COPYRIGHT.ghm-1.0
(included in the download packages)
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Command reference (on-line help texts):
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ghm-1.0.pdf
(included in the download packages)
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GENEHUNTER-TWOLOCUS
GENEHUNTER-TWOLOCUS is a modification of the
GENEHUNTER software
package version 1.3 (Kruglyak et al. 1996; Kruglyak and Lander 1998).
The program performs parametric and nonparametric multi-marker
linkage analysis of dichotomous traits with two autosomal diallelic
disease loci. It uses two unlinked marker maps with one disease
locus linked to each map. Like the single-disease-locus versions
GENEHUNTER-IMPRINTING and
GENEHUNTER-MODSCORE (please see
above), GENEHUNTER-TWOLOCUS allows for a parametric (LOD-score)
analysis with imprinting disease models. It can take into account
parent-of-origin effects at both loci.
In case of a parametric (LOD-score) analysis with two trait
loci, the parameters of the two-locus model (i.e., two disease
allele frequencies and 9 penetrances – or 16 penetrances if
imprinting should be modeled) need to be specified prior to the
analysis. It is possible to derive these parameters
from the best-fitting trait models that were obtained by a
single-trait-locus MOD-score analysis, e.g. with
GENEHUNTER-MODSCORE, at the two
loci.
For details regarding this issue, please refer to the article
by Strauch et al. ("How to model a complex trait. 2. Analysis with
two disease loci",
Human Heredity 56:200-211, 2003), in which the
corresponding formulae are given. A spreadsheet for OpenOffice and
MS-Excel as well as a C program, One-Two (written by
Manuel Mattheisen, e-mail:
mmattheisen@uni-bonn.de),
is provided (please see below) which implements these formulae.
It allows researchers to easily derive the parameters of the
two-locus trait model from the best-fitting single-locus parameters.
The optimized and parallelized version GENEHUNTER-TWOLOCUS PARALLEL,
as described by Dietter et al. ("Efficient two-trait-locus linkage
analysis through program optimization and parallelization: application
to hypercholesterolemia",
European Journal of Human Genetics 12:542-550, 2004),
can analyze larger pedigrees
than the previous version. In particular, the optimization of the
serial program, before parallelization, has resulted in a speed-up
of a factor of more than 10. Therefore, using the new
GENEHUNTER-TWOLOCUS PARALLEL version is already of benefit in the
context of a computer with a single processor. The parallelization
further decreases the computation time by a factor of the number of
processors (i.e., perfect or linear speed-up). In addition, with
this new version, the genetic positions of both trait loci are varied
on their respective marker maps, not just the position of the second
trait locus with the first one fixed, as before. The two-locus LOD
and NPL scores are conveniently prepared to be displayed in
three-dimensional plots, e.g. using
Gnuplot or any other graphics
package. Here is an example of such a plot, showing a two-locus LOD
score of 4.44 that has been obtained in a linkage
study of high factor VIII levels in venous thromboembolism
(Berger et al., "High factor VIII levels in venous thromboembolism
show linkage to imprinted loci on chromosomes 5 and 11",
Blood 105:638-644, 2005).
More information about GENEHUNTER-TWOLOCUS can be found in the files
INSTALL.ght and README_GHT_PARALLEL that are included in the archives
provided below.
Reference publications for GENEHUNTER-TWOLOCUS
Dietter J, Spiegel A, an Mey D, Pflug HJ, Al-Kateb H, Hoffmann K,
Wienker TF, Strauch K (2004):
Efficient two-trait-locus linkage analysis through program
optimization and parallelization:
application to hypercholesterolemia.
European Journal of Human Genetics 12:542-550
(Supplementary information).
Strauch K, Fimmers R, Kurz T, Deichmann KA, Wienker TF,
Baur MP (2000):
Parametric and nonparametric multipoint linkage analysis with imprinting
and two-locus-trait models: application to mite sensitization.
American Journal of Human Genetics 66:1945-1957.
Download
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GENEHUNTER-TWOLOCUS PARALLEL:
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| ghtp.tar.gz |
(for Unix systems, parallel and single-processor version)
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| ghtp.zip |
(for MS-Windows systems, parallel version) |
| ghtp_no_mpi.zip
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(for MS-Windows systems, single-processor version) |
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Installation instructions and copyright notice:
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INSTALL.ght-par /
COPYRIGHT.ght-par
(included in the download packages)
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The author of the optimized and parallelized version is
Johannes Dietter.
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GENEHUNTER-TWOLOCUS (old version):
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Installation instructions and copyright notice:
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INSTALL.ght-old /
COPYRIGHT.ght-old
(included in the download packages)
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Command reference (on-line help texts):
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ght.pdf
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The old version is mentioned here for completeness; even users
of computers with a single processor can run the faster
GENEHUNTER-TWOLOCUS PARALLEL version.
Original GENEHUNTER references
Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996):
Parametric and nonparametric linkage analysis: a unified multipoint
approach.
American Journal of Human Genetics 58:1347-1363.
Kruglyak L, Lander ES (1998):
Faster multipoint linkage analysis using Fourier transforms.
Journal of Computational Biology 5:1-7.
Markianos K, Daly MJ, Kruglyak L (2001):
Efficient multipoint linkage analysis through reduction of
inheritance space.
American Journal of Human Genetics 68:963-977.
Last update: September 12, 2008
