data processing

Data processing, data analysis, data classification...
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 22/09/13
  • Minor correction: 22/09/13

Ibex : C++ numerical library based on interval arithmetic and constraint programming

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 2.0.9 - 28/08/2013
  • License(s): LGPL - v3
  • Status: beta release
  • Support: maintained, ongoing development
  • Designer(s): Ibex team
  • Contact designer(s): gilles.chabert @ mines-nantes.fr
  • Laboratory, service: Universidad TĂ©cnica Federico Santa MarĂ­a (Chile)

 

General software features

This C++ library can be used to solve a variety of problems that can be formulated roughly as:

Find a reliable characterization with boxes (Cartesian product of intervals) of sets implicitely defined by constraints.

Where 'reliable' means that all sources of uncertainty should be taken into account, including:

  • approximation of real numbers by floating-point numbers,
  • round-off errors,
  • truncation linearization,
  • model parameter uncertainty,
  • measurement noise,
  • ...
Context in which the software is used

Tool for research in constraint programming.

Publications related to the software
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 22/09/13
  • Minor correction: 22/09/13

Norm_Est : fast and robust normal estimation for point clouds with sharp features

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 20130813 - 13/08/2013
  • License(s): GPL - v3
  • Status: stable release
  • Support: maintained, no ongoing development
  • Designer(s): Alexandre Boulc'h
  • Contact designer(s): boulc-ha @ imagine.enpc.fr
  • Laboratory, service:

 

General software features

This software computes the normal to the underlying surface at every point of a given point cloud. The algorithm does not smooth sharp angles while being as fast as the state of the art.

Context in which the software is used

Software used to obtain the results of publication [1], see also the slides of the presentation (on the web site).

Publications related to the software

[1] Alexandre Boulc'h and Renaud Marlet, Fast and Robust Normal Estimation for Point Clouds with Sharp Features,
Symposium of Geometry Processing 2012, Tallin, Estonia.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 19/09/13
  • Minor correction: 19/09/13
  • Index card author: Eric Hivon (IAP)
  • Theme leader : Dirk Hoffmann (Centre de Physique des Particules de Marseille (CPPM-IN2P3))

HEALPix : data analysis, simulation and visualisation on the sphere

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 3.11 - April 2013
  • License(s): GPL - GPLv2
  • Status: stable release
  • Support: maintained, ongoing development
  • Designer(s): Eric Hivon; Martin Reinecke; Krzysztof M. Gorski; Anthony J. Banday; Benjamin D. Wandelt; Emmanuel Joliet; William O'Mullane; Cyrille Rosset; Andrea Zonca
  • Contact designer(s): hivon at iap.fr
  • Laboratory, service: MPA (Garching, Allemagne), Caltech (Pasadena, CA,Etats-Unis), TAC (Copenhague, Danemark), ESAC (Madrid, Espagne), JPL (Pasadena, CA, Etats-Unis), ESO (Garching, Allemagne)

 

General software features

The HEALPix software implements the HEALPix (Hierarchical Equal Area iso-Latitude Pixelation) pixelation of the sphere. Initially developed for the simulation and analysis of ESA Planck satellite observations (dedicated to the study of the Cosmic Microwave Background (CMB) anisotropies, whose first results were delivered in March 2013), this software and its pixelation algorithm have become standard tools in the simulation and analysis of data on the sphere, including the NASA WMAP satellite, also dedicated to CMB observation, and the Pierre Auger ground based observatory for high energy cosmic rays, and are used for other astrophysical and geological studies.

Main features of the pixelation

At a given resolution, all HEALPix pixels have the same surface area, even if their shape varies slightly. Thanks to the hierarchical feature of the pixelation, upgrading its resolution to the next level simply amounts to divide each pixel into four sub-pixel of the same area. This allows quick and efficient upgrading and downgrading operations of existing maps.

Since the pixels are regularly spaced on iso-latitude rings, Spherical Harmonics can be computed very efficiently. The synthesis or analysis up to multipole Lmax  of a spherical data set containing Npix pixels is reduced from    Npix Lmax2   to   Npix½ Lmax2  compared to non iso-latitude pixelation.

Features of the software package

The represents data on the sphere, and enables analysis or simulation of these maps in (scalar or spin-weighted) Spherical Harmonics, as well as various kinds of statistical analyses and processing. Portable FITS files are used for input and output. The list of available functions includes:

  • generation of random maps (gaussian or not) from an arbitrary angular power spectrum,
  • computation of the angular power spectrum (or angular correlation function) of a map,
  • convolution of a spherical map with an arbitrary circular window,
  • tessellation of the sphere and pixel processing supported down to a pixel size of 0.4 milliarcseconds (equivalent to 3.5 1018 pixels on the sphere),
  • median filtering of a map,
  • search of local extrema in a map,
  • query of pixels located in user defined disks, triangles, polygons, ...
  • processing of binary masks to identify 'holes' in order to fill them, or to apodize masks,
  • visualization of HEALPix sky maps either on the whole sky (using Mollweide or orthographic projections) or on a patch (gnomic or cartesian projections),
  • output in Google Map/Google Sky and DomeMaster format.

The most expensive operations, such a Spherical Harmonics Transform have been carefully optimised and benefit from a shared memory parallelisation based on OpenMP.

Contents of the software package

The software is available in C, C++, Fortran90, IDL/GDL, Java and python. The following modules are provided in each of these languages:

  • a library of tools (subroutines, functions, procedures, modules, classes, ...depending on languages) covering most of the functionnalities described above, as well as supporting ancillary tools (eg, parameter file parsing),
  • a set of stand-alone facilities based on the library above and each implementing one of HEALPix major features (map generation or analysis, filtering, resolution udgrade or downgrade, visualization). These applications are generally run via an interactive dialog or an ASCII parameter file. Their source code can be used as a starting point for user specific developments,
  • an extensive PDF and/or HTML documentation describing in details the API, inner working and limitations of each tool and application.

Finally, some tools (interactive script and Makefile) are provided to manage and facilitate the compilation and installation of one or several of the libraries and facilities, for most combinations of hardwares, operating systems, compilers, ...

Third Party Developements

One can distinguish two kinds of third party developements (defined as not (yet) being part of the official HEALPix package described above):

  • new functionalities, for instance many tools based on Minkowski functionals, wavelets (iSAP, MRS, S2LET, SphereLab), or structure identification (DisPerSE) developed by various research teams can be applied to data stored in HEALPix format,
  • translations, re-implementations or wrapping of (some of) existing functionalities, for instance in Matlab/Octave (Mealpix) and Yorick (YHeal) are available. (See (almost) exhaustive list.)

Context in which the software is used

Software used for the analysis of Planck satellite data.
Data format supported by Aladin visualisation software to represent diffuse astronomical data on the sky.

Publications related to the software

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 11/09/13
  • Minor correction: 11/09/13

Signal separation : generation and separation of digital signals

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • System:
  • Current version: 2012
  • License(s): Proprietary licence
  • Status: internal use
  • Support: not maintained, no ongoing development
  • Designer(s): Elena Florian, Antoine Chevreuil, Philippe Loubaton.
  • Contact designer(s): Philippe.Loubaton @ univ-mlv.fr
  • Laboratory, service:

 

General software features

This sofware generates various kinds of signals produced by standard digital communication systems, and simulates their propagation into a multi-channel multi-paths propagation channel. A number of blind source separation algorithms are also implemented.

Context in which the software is used

This software has been released for the industrial contract Aintercom, this software is not distributed otherwise.

Publications related to the software
  • Elena Florian, Antoine Chevreuil, Philippe Loubaton. Blind source separation of convolutive mixtures of non circular linearly modulated signals with unknown baud rates. Signal Processing, 2012, 92, pp. 715-726.

  • P. Jallon, Antoine Chevreuil, Philippe Loubaton. Separation of digital communication mixtures with the CMA: case of various unknown baud rates. Signal Processing, 2010, 90 (9), pp. 2633-2647.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 11/09/13
  • Minor correction: 11/09/13

TreeCloud : building tree cloud visualizations from texts

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 1.3 - 13/12/2009
  • License(s): GPL
  • Status: under development
  • Support: maintained, ongoing development
  • Designer(s): Philippe Gambette ; Jean VĂ©ronis
  • Contact designer(s):

    P. Gambette

  • Laboratory, service:

 

General software features

TreeCloud generates a tree cloud from a text, that is a word cloud whose words are arranged around a tree which reflects their semantic proximity inside the text.

Context in which the software is used

The main application of the tree clouds built by TreeCloud is to provide a quick overview of the content of a text. It is also possible to use them for a deeper analysis of the texts, included in a textometric approach (text analysis using software tools and statistical methods). Then, the tree cloud will help the user to fomalize some hypotheses, or test them. It can therefore lead to use other textometric tools to confirm these hypotheses, or to visualize the results of the output of those tools.

Publications related to the software

Philippe Gambette and Jean VĂ©ronis: Visualising a Text with a Tree Cloud, In Locarek-Junge H. and Weihs C., editors, Classification as a Tool of Research, Proc. of IFCS'09 (11th Conference of the International Federation of Classification Societies) Studies in Classification, Data Analysis, and Knowledge Organization 40, p. 561-570, 2010.

Delphine Amstutz and Philippe Gambette (in French): Utilisation de la visualisation en nuage arboré pour l'analyse littéraire, Statistical Analysis of Textual Data (Proc. of JADT'10), p. 227-238, 2010.

Philippe Gambette, Nuria Gala and Alexis Nasr(in French): Longueur de branches et arbres de mots, Corpus 11, p. 129-146, 2012.

William Martinez and Philippe Gambette (in French): L'affaire du Médiator au prisme de la textométrie, Texto !, to appear, 2013.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 24/04/13
  • Minor correction: 24/04/13

X!TandemPipeline : edit, filter, merge and group your peptide/protein identifications from MS/MS mass spectra

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 3.3.0 - 7 juillet 2012
  • License(s): GPL - v3
  • Status: stable release
  • Support: maintained, ongoing development
  • Designer(s): Benoit Valot, Olivier Langella
  • Contact designer(s): olivier.langella@moulon.inra.fr
  • Laboratory, service:

 

General software features

X!TandemPipeline is a free software (GPL v3) that helps you to filter and group your peptide/protein identifications from MS/MS mass spectra.

Main features :

Context in which the software is used

X!TandemPipeline is designed for a day use by biologists. It performs MS identifications, filters and groups huge data very quickly.

Publications related to the software

Ludovic Bonhomme, Benoit Valot, Francois Tardieu, Michel Zivy. “Phosphoproteome Dynamics Upon Changes in Plant Water Status Reveal Early Events Associated with Rapid Growth Adjustment in Maize Leaves.” Molecular & Cellular Proteomics: MCP (July 10, 2012). http://www.ncbi.nlm.nih.gov/pubmed/22787273.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 18/04/13
  • Minor correction: 18/04/13

SVDetect : a tool to detect genomic structural variations from paired-end and mate-pair sequencing data

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 0.8 - 05/12/2011
  • License(s): GPL
  • Status: stable release
  • Support: maintained, no ongoing development
  • Designer(s): Bruno Zeitouni, Valentina Boeva
  • Contact designer(s): svdetect@curie.fr
  • Laboratory, service:

 

General software features

From NGS paired sequences and mapped onto a reference genome, SVDetect allows you to detect clusters of anomanously mapped pairs (with abnormal order, strand orientation or insert size of fragments), and to predict structural variants (SVs) such as large insertions, deletions, inversions, duplications or intra/inter-chromosomal translocations. SVDetect can also compare the results of SVs from different samples and to identify specific-sample SVs (Tumoral DNA vs Control DNA, for example).
SVDetect is compatible with any type of paired reads ("paired-end" or "mate-pair"), sequencing technology (Illumina, SOLiD, PGM, ...), or type of genome.
SVDetect can compute coverage profiles and to reveal loss or gains of genomic regions from the copy-number information.
It is available into a PERL Script and takes the BAM format as input.
SVDetect is also available at the Galaxy toolshed.

Context in which the software is used

SVDetect is an application for the isolation and the type prediction of intra- and inter-chromosomal rearrangements from paired-end/mate-pair sequencing data provided by the high-throughput sequencing technologies.
It was primarily tested in the context of whole genome resequencing projects from cancer cells, rich in chromosomal rearrangements.
SVDetect can also detect fusion genes from RNA-seq experiments.

Publications related to the software
  • SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data
    Bruno Zeitouni; Valentina Boeva; Isabelle Janoueix-Lerosey; Sophie Loeillet; Patricia Legoix-ne; Alain Nicolas; Olivier Delattre; Emmanuel Barillot, Bioinformatics 2010 26: 1895-1896, http://www.hal.inserm.fr/inserm-00508372
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 21/02/13
  • Minor correction: 22/02/13

GammaLib : C++ library for gamma-ray astronomy data analysis

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 00-07-00 - 11 January 2013
  • License(s): GPL - Version 3
  • Status: stable release
  • Support: maintained, ongoing development
  • Designer(s): JĂĽrgen Knödlseder
  • Contact designer(s): jurgen.knodlseder@irap.omp.eu
  • Laboratory, service: DESY (Deutsches Elektronen-Synchrotron, Hamburg), MPIK (Max-Planck Institute for Nuclear Physics, Heidelberg)

 

General software features

GammaLib is a self-contained, instrument independent, open source, multi-platform C++ library, that implements all code required for high-level science analysis of astronomical gamma-ray data. GammaLib is also wrapped into a Python module.

GammaLib does not rely on any third-party software, except of HEASARC's cfitsio library that is used to implement the FITS interface. Large parts of the code treat gamma-ray observations in an abstract representation, and do neither depend on the characteristics of the employed instrument, nor on the particular formats in which data and instrument response functions are delivered. Instrument specific aspects are implemented as isolated and well defined modules that interact with the rest of the library through a common interface. This philosophy also enables the joint analysis of data from different instruments, providing a framework that allows for consistent broad-band spectral fitting or imaging.

GammaLib contains the following modules:

  • a module for observation, data and instrument response function handling
  • a module for the definition of models (astrophysical source and background models)
  • a module for model fitting
  • a module for image handling
  • a module for the creation of ftools
  • a module for numerical computations
  • a module for linear algebra
  • a module with support functions for GammaLib classes
  • an interface for handling of FITS data
  • an interface for handling data in XML format
  • an interface for handling IRAF parameters

GammaLib is highly portable, requiring only a C++ compiler for building. The only dependency needed for operations is the cfitsio library that implement the FITS interface. If available, GammaLib can also benefit from an OpenMP support to perform parallel computations on multi-processor or multi-core machines.

All GammaLib functionalities are accessible via a C++ interface. GammaLib is also available as a Python module (version 2 and 3).

To enable the data analysis for a specific telescope, a dedicated module needs to be implemented that describes the format and the structure of the telescope's data, as well as its instrument response function. By default, GammaLib supports analysis of data from the Fermi/LAT telescope, the COMPTEL telescope, existing Cherenkov telescopes (H.E.S.S., MAGIC, VERITAS), and the future Cherenkov Telescope Array (CTA).

Context in which the software is used

GammaLib is used as basis of the ctools software, a set of executables that is proposed as the science analysis framework for the Cherenkov Telescope Array (CTA) project.

GammaLib is also employed for the analysis of Fermi/LAT data.

Publications related to the software

Knödlseder, J. 2011, GammaLib - A new framework for the analysis of Astronomical Gamma-Ray Data, submitted to arXiv (http://arxiv.org/abs/1110.6418)

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 29/08/12
  • Minor correction: 29/08/12

PFIM : population design evaluation and optimisation

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: PFIM INTERFACE 3.1 and PFIM 3.2.2 - March 2011
  • License(s): GPL
  • Status: stable release, under development
  • Support: maintained, ongoing development
  • Designer(s): Caroline Bazzoli, Thu Thuy Nguyen, Anne Dubois, Sylvie Retout, Emanuelle Comets, HervĂ© Le Nagard, France MentrĂ©
  • Contact designer(s): caroline.bazzoli@imag.fr, thu-thuy.nguyen@inserm.fr, france.mentre@inserm.fr
  • Laboratory, service:

 

General software features

PFIM (Population Fisher Information Matrix) is a R function dedicated to evaluation and optimisation of designs (number of subjects, number of samples per subject and their allocation in time) for nonlinear mixed effects models (population approach). This function is based on the developpement of an approximation of the Fisher information matrix in these models.

Two latest versions of PFIM are currently available :

  • a graphical user interface package using the R software (PFIM Interface 3.1),
  • an R script version (PFIM 3.2.2) requiring some knowledge in R use but which benefits of the latest methodological developments performed in the research team.
Context in which the software is used

PFIM is mainly used to design informative studies in pharmacology for the analyses of dose-concentration-effect (pharmacokinetics/pharmacodynamics) relationtionships of drugs.

PFIM is subject to statistical research (developement of the Fihser Infromation matrix, UMR 738 INSERM-Université Paris-Diderot) but also to pharmacology research.

Publications related to the software

Methodology

  • Nguyen TT, Bazzoli C, MentrĂ© F. Design evaluation and optimisation in crossover pharmacokinetic studies analysed by nonlinear mixed effects models, Nguyen TT, Bazzoli C, MentrĂ© F, 2011, [Epub ahead of print].
  • Bazzoli C, Retout S, MentrĂ© F. Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0, Computer Methods and Programs in Biomedicine, 2010, 98 : 55-65.
  • Retout S, Comets E, Bazzoli C, MentrĂ© F. Design optimisation in nonlinear mixed effects models using cost functions:application to a joint model of infliximab and methotrexate pharmacokinetics, Communication in Statistics: Theory and Methods, 2009, 38 : 3351–3368.
  • Bazzoli C, Retout S, MentrĂ© F. Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model, Statistics in Medicine, 2009, 28 : 1940-1956.
  • Retout S, Comets E, Samson A, MentrĂ© F. Design in nonlinear mixed effects models: optimization using the Fedorov-Wynn algorithm and power of the Wald test for binary covariates, Statistics in Medicine, 2007, 26: 5162-5179.
  • Retout S, MentrĂ© F. Optimisation of individual and population designs using Splus, Journal of Pharmacokinetic and Pharmacodynamics, 2003, 30: 417-443.
  • Retout S, MentrĂ© F. Further developments of the Fisher information matrix in nonlinear mixed-effects models with evaluation in population pharmacokinetics, Journal of Biopharmaceutical Statistics, 2003, 13: 209-227.
  • Retout S, MentrĂ© F, Bruno R. Fisher information matrix for nonlinear mixed-effects models: evaluation and application for optimal design of enoxaparin population, Statistics in Medicine, 2002, 21: 2623-2639.
  • Retout S, Duffull S, MentrĂ© F. Development and implementation of the population Fisher information matrix for evaluation of population pharmacokinetic designs, Computer Methods and Programs in Biomedicine, 2001, 65: 141-151.
  • MentrĂ© F, Mallet A, Baccar D. Optimal design in random-effects regression models, Biometrika, 1997, 84 : 429-442.

Applications of PFIM

  • Delavenne X, Zufferey P, Nguyen P, Rosencher N, Samama C.M,Bazzoli C, Mismett P, Laporte S. Pharmacokinetics of fondaparinux 1.5 mg once daily in a real-world cohort of patients with renal impairment undergoing major orthopaedic surgery. Pharmacokinetics and disposition, 2012, [Epub ahead of print].
  • Sherwin CM, Ding L, Kaplan J, Spigarelli MG, Vinks AA. Optimal study design for pioglitazone in septic pediatric patients. Journal of Pharmacokinetics and Pharmacodynamics, 2011, 38 : 433-447.
  • Guedj J, Bazzoli C, Neuman A.U, MentrĂ© F. Design evaluation and optimization for models of hepatitis C
    viral dynamics. Statistics in Medicine, 2011, 30 : 1045-1056.
  • Bazzoli C, Retout S, MentrĂ© F. Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0, Computer Methods and Programs in Biomedicine, 2010, 98 : 55-65.
  • Retout, S., Comets, E., Bazzoli, C. et MentrĂ©, F. Design optimisation in nonlinear mixed effects models using cost functions: application to a joint model of infliximab and methotrexate pharmacokinetics, Communication in
    Statistics: Theory and Methods, 2009, 38 : 3351–3368.
  • Bazzoli C, Retout S, MentrĂ© F. Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model, Statistics in Medicine, 2009, 28 : 1940-1956.
  • Retout S, Comets E, Samson A, MentrĂ© F. Design in nonlinear mixed effects models: optimization using the Fedorov-Wynn algorithm and power of the Wald test for binary covariates, Statistics in Medicine, 2007, 26 : 5162-5179.
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 20/01/12
  • Minor correction: 20/01/12

QTLMap : detection of QTL from experimental designs in outbred population

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 0.8.3 - 14 october 2010
  • License(s): CeCILL
  • Status: beta release
  • Support: maintained, ongoing development
  • Designer(s): Pascale Le Roy, Jean-Michel Elsen, Helene Gilbert, Carole Moreno, Andres Legarra, Olivier Filangi
  • Contact designer(s): olivier.filangi@rennes.inra.fr
  • Laboratory, service:

 

General software features

Description

QTLMap 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 exact as possible. QTLMap is able to deal with large numbers of markers (SNP) and traits (eQTL).

Functionnalities

  • 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 the analysis
  • Gaussian, discrete or survival (Cox model) data
  • Familial heterogeneity of variances (heteroscedasticity)
  • 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 trait values
  • Computation of power and accuracy of your design or any simulated design
Context in which the software is used

QTLMap source code is available under the CeCILL version 2.0 license, a GPL like license.

Utilisateurs

This software is used by genetic researchers to detect a region of the genome that controls an agronomic trait

Cluster Infrastructures

Software dependencies

Installation

  • Suite gcc (>=4.4)
  • CMake 2.6.4

Support

Users mailing list : inscription

Publications related to the software

Legarra A, Fernando RL, 2009. Linear models for joint association and linkage QTL mapping. Genet Sel Evol., 41:43.

Elsen JM, Filangi O, Gilbert H, Le Roy P, Moreno C, 2009. A fast algorithm for estimating transmission probabilities in QTL detection designs with dense maps. Genet Sel Evol., 41:50.

Gilbert H., Le Roy P., Moreno C., Robelin D., Elsen J. M., 2008. QTLMAP, a software for QTL detection in outbred population. Annals of Human Genetics, 72(5): 694.

Gilbert H, Le Roy P., 2007. Methods for the detection of multiple linked QTL applied to a mixture of full and half sib families. Genet Sel Evol., 39(2):139-58.

Moreno C.R., Elsen J.M., Le Roy P., Ducrocq V., 2005. Interval mapping methods for detecting QTL affecting survival and time–to–event phenotypes. Genet. Res. Camb., 85 : 139-149.

Goffinet B, Le Roy P, Boichard D, Elsen JM, Mangin B, 1999. Alternative models for QTL detection in livestock. III. Heteroskedastic model and models corresponding to several distributions of the QTL effect.. Genet. Sel. Evol., 31, 341-350.

Mangin B, Goffinet B, Le Roy P, Boichard D, Elsen JM, 1999. Alternative models for QTL detection in livestock. II. Likelihood approximations and sire marker genotype estimations. Genet. Sel. Evol., 31, 225-237.

Elsen JM, Mangin B, Goffinet B, Boichard D, Le Roy P, 1999. Alternative models for QTL detection in livestock. I. General introduction. Genet. Sel. Evol., 31, 213-224

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