Result for 078916F48256774E64CFD90A4D544629EE74E6F7

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/Meta/package.rds
FileSize1203
MD56D40584416048BDFCDD8D7582DFE07F2
SHA-1078916F48256774E64CFD90A4D544629EE74E6F7
SHA-25677A5020AE627C70EF7478553219C72724A6AF3C6FDEC204338FC18E8666C0400
SSDEEP24:XWhlaTBWP8fdJHdmcvC6LXqO4cYZa7E+i9x3A6pgPTTiD:XKmbJZuxXdCP3iD
TLSHT13521B7F4C1DA84CA9450D86A6A95F490A95DFCA5B0000EC23569B58A7A3024D0F38A7B
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize5520864
MD525DD68EBA7834EA1CAC3A160ADD00CE1
PackageDescriptionGNU 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.
PackageMaintainerDebian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageNamer-cran-qtl
PackageSectiongnu-r
PackageVersion1.50-1
SHA-174746C3DB1B0378E5C41C9D0EAC282FB7F159959
SHA-256FBAEBE4C45E6514AB239E8880451EA6115F63196DF6CE0D0F1E6D6DED354EE99