A QTL mapping experiment consists in a genetic linkage map and a set of quantitative trait loci (QTL) which have been detected and positioned onto the genetic linkage map.
MetaQTL is a suite of programs designed to carry out meta-analysis of QTL mapping experiments.
This package is composed by several programs written in pure Java. These programs can perform various tasks, including reformatting, analyzing data and visualizing the results of the analyses.
Presently the programs can handle data from backcross, intercrosses and recombinant inbreds, as well as a few other experimental designs.
Get MetaQTL and give it a try to see what it’s all about!

There are five meta-analysis programs included in MetaQTL Cracked Accounts. Each one of these programs works as a wrapper over one of the core programs listed below, or they are specializations of the general purpose programs.
MetaQTL Activation Code_regression – fits a model to the data and estimates the parameters of the model from the observations. This can include an additive and/or dominance model.
MetaQTL_mle – fits an MLE (Maximum Likelihood Estimator) of a particular statistical model to the data. The model is chosen from a predefined set of models.
MetaQTL_mimic – mimic the output of a genetic map calculation in other programs using a predefined set of input parameters. For example, with MetaQTL_mimic we can export a marker-based map to a GAMMA/QTL/Express-like program.
MetaQTL_mimic_update – like the previously mentioned, but it allows the user to update the parameters of the model from a file. It is the meta-analysis update function. This one is specially useful if MetaQTL_regression is being used.
MetaQTL_mimic_map_gen – mimic the output of a QTL mapping calculation program. We can export a QTL-based map to a QTL/Express-like program. This is the meta-analysis update function.
MetaQTL_query – a simple query, MetaQTL_mapgen and MetaQTL_mimic_map_gen generate a file with the list of the marker names in a given position, while MetaQTL_mimic and MetaQTL_mimic_update generate a file with the data, in a specific position.
Some files may be read by more than one program, depending on what was asked for.
The programs have been tested against data in standard formats: NeXus, S.A.G., MatFile, etc.
Genetic QTL mapping programs:
MetaQTL_qtl – a program for backcross and intercrosses. It estimates a model for the QTL from the data.
MetaQTL_mimic_map_qtl – a program for QTL mapping backcrosses and intercrosses. It estimates the model from the data using the genotypes of the parents.
MetaQTL_mimic_map_qtl_update – update the model parameters from the

This program reads a key macro file and converts it to GWAFList format. GWAFList is a lightweight, powerful data format for storing QTL mapping data.
It is the successor of the qtl file format.
The format of GWAFList is very simple, and only a few elements are required: one chromosome name, a list of markers and their positions, and the list of phenotypic traits. The order of these elements is not important.
This program also converts qtl macro data to GWAFList.
Further information can be found at:
getMetaQTL.org/qtl/gwaf
Get MetaQTL and give it a try to see what it’s all about!
KEYRESULT Description:
This program creates a GWAFList file from a QTL mapping result.
It can convert two kinds of results: one from backcross, intercrosses and recombinant inbreds; and one from EMMAX or JoinMap.
Further information can be found at:
getMetaQTL.org/qtl/gwaf
Get MetaQTL and give it a try to see what it’s all about!
KEYCOMMAND Description:
This program reads the current execution state, and writes the key command text.
KEYPROGRAM Description:
This program reads the current execution state, and writes the key program text.
KEYGEN Description:
This program reads the current execution state, and writes the key gen text.
KEYUPDATE Description:
This program reads the current execution state, and writes the key update text.
KEYGENEX Description:
This program reads the current execution state, and writes the key gen ex text.
KEYSTOREDATA Description:
This program reads the current execution state, and writes the key stored data text.
KEYAURORA Description:
This program reads the current execution state, and writes the key aurea text.
KEYEVENTURNO Description:
This program reads the current execution state, and writes the key eventurno text.
KeyTrigger Program Description:
This program reads the current execution state, and writes the key trigger program text.
KEYUSEFUL Description:
This program reads the current execution state, and writes the key useful text.
KEYEXAMPLES Description:
This program reads the current execution state, and writes the key examples text.
KEYMETADATA Description:
77a5ca646e

MetaQTL is a Java package designed to analyse and display results from QTL mapping experiments. It can deal with
different experimental designs, including backcross, intercross and RILs. In order to show all the power of MetaQTL,
the users will be required to use a set of (usually thousands) of marker loci that are genotyped across the genome
of a set of organisms.
MetaQTL provides a set of programs to perform different tasks, such as the following:

1. Produce a genetic linkage map of the organisms and their genotypes at the marker loci.

2. Perform a QTL analysis of a single experiment or combine several to get a single map.

3. Detect and display the QTL in the genetic linkage map.

4. If desired, perform a meta-analysis of a set of QTL maps.

5. Save and show the genetic linkage map produced by MetaQTL.

6. Visualize the marker loci and QTL in the graphical form of a Genetic Linkage Map.

MetaQTL currently supports backcross, intercross and RILs experiments as well as some experimental designs where the parents are
fully inbred. The latter situations include, for example, outbred populations, as well as experimental designs where
markers are distributed randomly along the genome.

In order to perform these tasks, MetaQTL uses a graphical user interface (GUI) in which the user specifies the
parameters for each analysis, which are stored as objects in the system and are reused by the various programs of
MetaQTL. This way of performing analyses saves a lot of time and provides a robust tool for performing these tasks.

MetaQTL is based on the concept of ‘designs’. A design is a set of experiments that have been analyzed together and
give rise to a set of QTL maps. In order to perform a QTL analysis using MetaQTL, the user must specify a set of
experimental designs, the marker loci (e.g. [SSR]), the number of parents of each cross (e.g. 3) and the QTL
discovery method (e.g. either LOD or Ht).

Once the designs have been specified, the user must provide a genetic linkage map of the organisms (either in
consensus or as a collection of groups, where a group is represented by a

———————-
The software is a collection of several programs written in Java.
It performs meta-analysis of quantitative trait loci mapping experiments.
There are three main programs included in the software package,
* MetaQTL, a meta-analysis software for mapping experiments. It uses
generic multi-marker analyses.
* MetaGen, a program to carry out interval mapping. It uses
meta-analysis of pooled family information, for “random effects”.
It uses GLM and LASSO. It is also able to handle additive,
dominant and epistatic effects.
* MetaChiSq, a program for performing and analyzing meta-analysis
of qualitative traits. It uses GLM, LASSO and REML.
All programs are written using the JRI 4.0 (JAva 6) package,
the Open Source Java reflection mechanism.
Some parts of the programs are also able to use the JRI 2.0 package,
but all features are exposed through the former package.
* MetaQTL supports the IxM/FxM procedure for backcross,
F2xM and MxF1 procedures for intercrosses,
JIC (JaIxChit) procedures for recombinant inbred lines.
A few other procedures are supported by the program,
please check the MANUAL for more details.
* MetaQTL can handle data for bi-allelic traits, by allowing two
alleles in each QTL. There are commands to select the alleles,
and the programs will take these alleles into account.
* MetaQTL runs well on Windows XP, as well as on other Unix-like systems.
It works also on MacOS X, but it’s not tested on these systems.

Requirements:
—————–
* To run the programs, you need the Oracle JDK 1.4.2.
* Java SE 6 on Windows (or 7 if you have Oracle, but it’s not
required).
* Java SE 6 (or 7 if you have Oracle) on Unix-like systems.
* Any Java SE 6 compliant JRE is required on Windows.
* Any Java SE 6 compliant JRE is required on Unix-like systems.
* Java SE 4.0 or higher is required to run MetaGen.

INSTALLATION

Unpack the software.
Inside the MetaQTL directory, run
java -jar Install.jar
This will add the jar files to your “classpath”, and you can run the
software without any special installation.

To run the programs, you need the Oracle JDK 1.4.2.
* On Windows, download the

Memory: 64 MB
Processor: PIIx4 550MHz
Video: GeForce 8800GTX / ATI Radeon HD2900XT
Dimensions: 800×600
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