Ignacy Misztal

dblp:37/1164 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › statistical genetics
association analysis
0.012004
Qxpak: a versatile mixed model application for genetical genomics and QTL analyses · Bioinform. 2004
Bioinformatics and computational biology › statistical genetics › quantitative trait locus mapping
genetical genomics
0.012004
Qxpak: a versatile mixed model application for genetical genomics and QTL analyses · Bioinform. 2004
Bioinformatics and computational biology › statistical genetics
quantitative trait locus analysis
0.012004
Qxpak: a versatile mixed model application for genetical genomics and QTL analyses · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

multitrait analysis · 0.0mixed model · 0.0
YearPublicationVenuePosition
2011 Qxpak.5: Old mixed model solutions for new genomics problems
abstract
BACKGROUND: Mixed models have a long and fruitful history in statistics. They are pertinent to genomics problems because they are highly versatile, accommodating a wide variety of situations within the same theoretical and algorithmic framework. RESULTS: Qxpak is a package for versatile statistical genomics, specifically designed for sophisticated quantitative trait loci and association analyses. Multiple loci, multiple trait, infinitesimal genetic effects, imprinting, epistasis or sex linked loci can be fitted. The new version (v. 5) allows us, among other new features, to include either relationship matrices obtained with molecular information or user defined matrices that can be read from an input file. This feature can be used for genome selection or - more importantly - to correct for population structure in association studies. In crosses, two parental lines, not necessarily inbred, can be accommodated. CONCLUSIONS: This software aims at simplifying statistical genetic analyses implementing a coherent and unified approach by mixed models. It provides a tool that can be used in a wide variety of situations with ample genetic and statistical modeling flexibility. The software, a complete manual and examples are available at http://www.icrea.cat/Web/OtherSectionViewer.aspx?key=485&titol=Software:Qxpak.
Miguel Pérez-Enciso, Ignacy Misztal
BMC Bioinform.2
2004 Qxpak: a versatile mixed model application for genetical genomics and QTL analyses
abstract
MOTIVATION: Current methodology and software for quantitative trait loci (QTL) analyses do not use all available information and are inadequate to deal with the huge amount of QTL analyses to be needed in forecoming genetical genomics' studies. RESULTS: We show that a mixed model statistical framework provides a very flexible tool for QTL modeling in a variety of populations, be it a cross between inbred lines, a within population study, or experiments involving a mixture of populations or crosses. The software allows multitrait and multiQTL analyses, inclusion of infinitesimal genetic value and a batch multitrait option suitable for genetical genomics studies. It also allows massive association studies between single nucleotide polymorphisms and the trait(s) of interest. AVAILABILITY: A software (Qxpak), together with a manual and example files, is freely available for research purposes. So far, the compiled program is available for linux systems, the windows version will follow soon. See http://www.icrea.es/pag.asp?id=Miguel.Perez
Miguel Pérez-Enciso, Ignacy Misztal
Bioinform.2