Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	AE9DB3010DCFD944ACAAC39FF05B2D52
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	Koji
PackageName	R-qtl
PackageRelease	1.fc17
PackageVersion	1.23.16
SHA-1	DC2E2BA342DD661936C716E03C86328A892F653E
SHA-256	A8D58334D58CF3ED24835084602BB4C96FCA5EBAD3B716403F231124E97043C7

Key	Value
MD5	651AA4E2CBB555F187E90CE919943F32
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	Koji
PackageName	R-qtl
PackageRelease	1.fc17
PackageVersion	1.23.16
SHA-1	868EEDD1EB2E528A8EE1C51C9F79D8D581C4E007
SHA-256	B4802867C0A232DD30A7219108DB4D8B1FB61A0BE3DC096F60829292EDC1C86F