Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

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
MD5	DA51743DD1D33DAA2749F42B82EC793E
PackageArch	ppc
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	673CDFC0660BC20C3479DE9B42A79F881FE738F3
SHA-256	A1B32275539008744E7123FA7C0C3DEFE6DE86C7B47530EA872B71A6BB7BE23C

Key	Value
MD5	A92612FBDFEBE3E5E3F43A0F93982C2E
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.fc20
PackageVersion	1.28.19
SHA-1	F5DC36798FBF4B7BCCFF0C0A91F84D0C0918900A
SHA-256	391BB0821FE5DF69679E826DF746A4D52852554B3692C229E35BC7B9FDDF66CD

Key	Value
MD5	695643DDC2534B9AE4C89CBFD97972A2
PackageArch	s390x
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	2C74DCF84B133BA001F040C752C0FB327C41EEAA
SHA-256	ACF372F6672E8E1B9EF6C0D2915A9197303D3C1808B0A8A935A65E248BE32C63