is a software dedicated to the
detection of QTL from experimental
designs in outbred population.
QTLMap software is developed by the Animal Genetics
Division at INRA (French National Institute for
Agronomical Research). The statistical techniques used are linkage
analysis (LA) and linkage disequilibrium linkage analysis (LDLA) using
interval mapping. Different
versions of the LA are proposed from
a quasi Maximum Likelihood approach to a fully linear
(regression) model. The LDLA is a regression approach (Legarra and
Fernando, 2009). The population may be sets of half-sib families or
mixture of full- and half- sib families.
The computations of Phase and
Transmission probabilities are optimized to be rapid and as
possible. QTLMap is able to deal with large numbers of markers (SNP)
and traits (eQTL).
The aim of QTLMap
developers is to propose various genetic models depending on
the number of QTL alleles segregating (biallelic in crosses
between monomorphic breeds, biallelic without hypothesis on the origin,
multiallelic, haplotype identity),
the number of QTL segregating (one, two linked, several
the number of traits under the QTL influence. The trait
determinism may vary depending on
the trait distribution (gaussian trait, survival trait or
the interactions between the QTL and fixed effects or other
the residual variance structure (homo- or heteroskedasticity
for half-sib families).
Due to differences with
the asymptotical conditions from the chi2 theory, the test statistic
significance are evaluated either through numerical approximations, or
through empirical calculations obtained from permutations or
simulations under the null hypothesis.
QTLmap is written in fortran 95 and use the OpenMP API (Parallel
Programming). The fully linear model approach is also implemented in CUDA.
to now, the following functionnalities have been implemented :
QTL detection in half-sib families
or mixture of full- and half-sib families
One or several linked QTL
segregating in the population
Single trait or multiple trait
Nuisance parameters (e.g. sex,
batch, weight...) and their interactions with QTL can be included in
Gaussian, discrete or survival
(Cox model) data
Familial heterogeneity of variances
Can handle eQTL analyses
Computation of transmission and
phase probabilities adapted to high throughput genotyping (SNP)
Empirical thresholds are estimated
using simulations under the null hypothesis or permutations of
Computation of power and accuracy of your design or any
Pascale Le Roy, Jean-Michel Elsen, Helene
Gilbert, Carole Moreno, Andres Legarra, Olivier Filangi
This project is funded by European project(SABRE) and the ANR(Rules
QTLMap source code is available under the CeCILL version 2.0 license, a
GPL like license.
MinGW or MinGW-w64 runtime environment. Download the The Bundle installer TDM-GCC
distribution and install "The TDM-GCC Recommanded, All packages"
With the density of current chips, it is difficult (or impossible) to calculate the rejection thresholds and thus to compare
the maximum likelihood ratio test found at a given position. In partnership with INRIA, a new implementation of QTLMap was
developed to compute the QTL effects in family and/or population
designs, using the CUDA language developed by NVIDIA for GPU cards.
These new implementations can provide a gain up to 50 folds compare to the multithreaded CPU version.
- 2200 progenies phenotyped, 20 sires, 200 dams, 2000 SNPs (chromosome size: 1 Morgan)
- the step of the anlysis is 1 cM.
- number of tested positions: 100
- number of simulations: 1000
You need to install the following tools to compile and build a