Results 1 to 10 of about 29,606 (168)
R/qtl: high-throughput multiple QTL mapping [PDF]
Bioinformatics, 2010 AbstractMotivation: R/qtl is free and powerful software for mapping and exploring quantitative trait loci (QTL). R/qtl provides a fully comprehensive range of methods for a wide range of experimental cross types. We recently added multiple QTL mapping (MQM) to R/qtl.
Danny Arends +3 more
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Behavior Genetics, 2004 The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well ...
Basrak, B. +4 more
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QTL Mapping to QTL Cloning: Mice to the Rescue [PDF]
Genome Research, 1997 With the availability of dense, highly informative marker maps, it has recently become feasible to map genes (Quantitative Trait Loci or QTL) accounting for part of the heritability of continuously distributed traits in experimental crosses as well as outbred populations. QTL mapping efforts have almost invariably revealed a limited number of loci with
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R/qtl: QTL mapping in experimental crosses
Bioinformatics, 2003 Abstract Summary: R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental populations derived from inbred lines. It is implemented as an add-on package for the freely-available statistical software, R, and includes functions for estimating genetic maps, identifying genotyping errors, and
Karl W. Broman +3 more
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, 2006 The study of the intraspecific natural variation existing in Arabidopsis provides a useful resource for the dissection of its genome at the functional, ecological, and evolutionary levels. A major step in these studies is the identification and location of quantitative trait loci (QTLs) determining the variation for trait(s) of interest, so-called QTL ...
Alonso-Blanco, C. +2 more
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Exome QTL-seq maps monogenic locus and QTLs in barley [PDF]
BMC Genomics, 2017 QTL-seq, in combination with bulked segregant analysis and next-generation sequencing (NGS), is used to identify loci in small plant genomes, but is technically challenging to perform in species with large genomes, such as barley. A combination of exome sequencing and QTL-seq (exome QTL-seq) was used to map the mono-factorial Mendelian locus black ...
Hiroshi Hisano +4 more
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Serious limitations of the QTL/Microarray approach for QTL gene discovery [PDF]
BMC Biology, 2010 Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL). However, the effectiveness of this approach has not been assessed.
Verdugo, Ricardo A +3 more
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PLoS Genetics, 2010 Natural selection sculpts phenotypes to enable adaptation to local conditions. Biologists have long been interested in the phenotypic and molecular response to selection, but we still know little about the genetic basis of adaptation. With continuing improvements in molecular technologies, we now have the tools to investigate the genes that underlie ...
Anderson, Jill T, Mitchell-Olds, Thomas
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Trends in Genetics, 1995 In the past 10 years, interest in applying the tools of molecular genetics to the problem of increasing world rice production has resulted in the generation of two highly saturated, molecular linkage maps of rice, and the localization of numerous genes and quantitative trait loci (QTLs).
S R, McCouch, R W, Doerge
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QTL MatchMaker: a multi-species quantitative trait loci (QTL) database and query system for annotation of genes and QTL [PDF]
Nucleic Acids Research, 2006 Identifying genes that underlie quantitative trait loci (QTL) is a challenging task. Here, we present a new QTL software system, named QTL MatchMaker. The system is designed to integrate and mine QTL information across human, mouse and rat genomes and to annotate functional genomic data.
Kremena V. Star +3 more
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