Parents (Total: 135)

The searched file hash is included in 135 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	4202324
MD5	99686B1BD763235E671CBBB2E30D1BBE
PackageDescription	GNU R package for genetic marker linkage analysis R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. It is implemented as an add-on-package for the freely available and widely used statistical language/software R (see http://www.r-project.org). . The development of this software as an add-on to R allows one to take advantage of the basic mathematical and statistical functions, and powerful graphics capabilities, that are provided with R. Further, the user will benefit by the seamless integration of the QTL mapping software into a general statistical analysis program. The goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. . A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. The main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses were implemented. . The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation.
PackageMaintainer	Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
PackageName	r-cran-qtl
PackageSection	gnu-r
PackageVersion	1.40-8-1
SHA-1	012F6E3BB53279E9B6AABD81E2BC50BBF1E2FF8F
SHA-256	660B67D4C1B29086E127E03045A7292F1AA49F0B1B72BF9DF2DCB973D7B813FD

Key	Value
MD5	B639DFFE61E1BA6AA9050B098A25F638
PackageArch	x86_64
PackageDescription	R-qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. Our goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. We have implemented the main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses. The current version of R-qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation and Haley-Knott regression.
PackageMaintainer	Fedora Project
PackageName	R-qtl
PackageRelease	1.el8
PackageVersion	1.46.2
SHA-1	0328667C94A7E2301C3B51FE383929AAA7246045
SHA-256	1BB737356F4E368E1A83ACBDA7A76A47119BB47F30210903C2F44537DB537D02

Key	Value
FileSize	4076788
MD5	5DC9592A5A297E575744E0E854D23702
PackageDescription	GNU R package for genetic marker linkage analysis R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. It is implemented as an add-on-package for the freely available and widely used statistical language/software R (see http://www.r-project.org). . The development of this software as an add-on to R allows one to take advantage of the basic mathematical and statistical functions, and powerful graphics capabilities, that are provided with R. Further, the user will benefit by the seamless integration of the QTL mapping software into a general statistical analysis program. The goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. . A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. The main HMM algorithms were implemented, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses. . The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-qtl
PackageSection	gnu-r
PackageVersion	1.27-10-1
SHA-1	04B33AD1689247407376A95D5A325F07047C266C
SHA-256	93CF1870DE7169A8D627DCE20994EF6DD138F0C8F86D1ED764A1D3570B3D9921

Key	Value
FileSize	5022684
MD5	994F37C529B630C00FF8CE7C540C28B5
PackageDescription	GNU R package for genetic marker linkage analysis R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. It is implemented as an add-on-package for the freely available and widely used statistical language/software R (see http://www.r-project.org). . The development of this software as an add-on to R allows one to take advantage of the basic mathematical and statistical functions, and powerful graphics capabilities, that are provided with R. Further, the user will benefit by the seamless integration of the QTL mapping software into a general statistical analysis program. The goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. . A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. The main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses were implemented. . The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-qtl
PackageSection	gnu-r
PackageVersion	1.37-11-1
SHA-1	0765EF32CCED8DFFBE9D15F85B426C96ACC089CF
SHA-256	56C37B4EE4F9A10B11445CCD5433525A616C972DEC9552E2E31A1AB067B3D457

Key	Value
MD5	8B59A3225F63F316459C8D7A91EA7D9F
PackageArch	s390
PackageDescription	R-qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. Our goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. We have implemented the main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses. The current version of R-qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation and Haley-Knott regression.
PackageMaintainer	Fedora Project
PackageName	R-qtl
PackageRelease	1.fc17
PackageVersion	1.23.16
SHA-1	0BD9A500120CE08299026578724AA194E6AEF3B5
SHA-256	3023506962AC155D70A86683FE6005E1A1DD3BB2ADBB2CFA05EA85EC6A58959A

Key	Value
MD5	3CAE8DDBDD3C8C530F738A2077465F2E
PackageArch	ppc64le
PackageDescription	R-qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. Our goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. We have implemented the main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses. The current version of R-qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation and Haley-Knott regression.
PackageMaintainer	Fedora Project
PackageName	R-qtl
PackageRelease	1.el8
PackageVersion	1.46.2
SHA-1	0D5F3B4D956E5DFB36F8A429B1A55CA830FB5F9D
SHA-256	93964834B8DA052B4E3DF741CCD37F9DE5666728633F565476D7E23DFE0EC66A

Key	Value
FileSize	5512124
MD5	C300B6A622E3E70B72373E196A71AE51
PackageDescription	GNU R package for genetic marker linkage analysis R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. It is implemented as an add-on-package for the freely available and widely used statistical language/software R (see http://www.r-project.org). . The development of this software as an add-on to R allows one to take advantage of the basic mathematical and statistical functions, and powerful graphics capabilities, that are provided with R. Further, the user will benefit by the seamless integration of the QTL mapping software into a general statistical analysis program. The goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. . A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. The main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses were implemented. . The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-qtl
PackageSection	gnu-r
PackageVersion	1.44-9-1
SHA-1	0E17D939F22C3DB6A41069624595EF4204B80D4B
SHA-256	1BA3FC9194A6409F75539F371E21FBF8C55A8543C1B363371F5D19FE637C475E

Key	Value
MD5	7E11E63E211156249326E0E8EC466F4D
PackageArch	ppc64
PackageDescription	R-qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. Our goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. We have implemented the main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses. The current version of R-qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation and Haley-Knott regression.
PackageMaintainer	Fedora Project
PackageName	R-qtl
PackageRelease	1.fc20
PackageVersion	1.28.19
SHA-1	0EC3C659ABDD78EFEF862C7193B80B5D080DF978
SHA-256	255BE44F551362192BE44CDB096023CF7B2098E57104F23A5660848A5F6C619A

Key	Value
FileSize	5515160
MD5	C3DC3AF48D24EE23D47621165BAE2D05
PackageDescription	GNU R package for genetic marker linkage analysis R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. It is implemented as an add-on-package for the freely available and widely used statistical language/software R (see http://www.r-project.org). . The development of this software as an add-on to R allows one to take advantage of the basic mathematical and statistical functions, and powerful graphics capabilities, that are provided with R. Further, the user will benefit by the seamless integration of the QTL mapping software into a general statistical analysis program. The goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. . A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. The main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses were implemented. . The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-qtl
PackageSection	gnu-r
PackageVersion	1.50-1
SHA-1	14243A7D65A38B9D9FDD01FE23CA8198E37E7194
SHA-256	D384B40D18182758C1229BC6FF90481DA48F8755E1DEA9D5A3A68DAAC3B3AFB5

Key	Value
MD5	9750DF82F0E4D027717DADD269E8C88E
PackageArch	ppc64
PackageDescription	R-qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. Our goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing. A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. We have implemented the main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses. The current version of R-qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation and Haley-Knott regression.
PackageMaintainer	Fedora Project
PackageName	R-qtl
PackageRelease	1.fc22
PackageVersion	1.36.6
SHA-1	1C0CEA23687BC14326460A77AF3D88F8C2BDE609
SHA-256	87A88C4D92F5E4F30692F4BD15B168527AC40F3BD927399BE316E074D396F6CB