Result for 04B70A1381665B46187B083BC6C59ABDA7521AAC

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/help/qtl.rdb
FileSize767421
MD50449ED688EC72829387373E3846E8A04
SHA-104B70A1381665B46187B083BC6C59ABDA7521AAC
SHA-256742E4AFB49F8A68D51DFBA953437AB7974D2021CE42773C81CF5F356E5EDCE56
SSDEEP12288:ANJDtrtf4PJR2Qkovio13GfAXB41cYbtXw3u/pxPSDULiCq5HKCMOLDquf/wEhBl:AnDRqz2Qkovio13GMGVbtAe/CH3WuHw0
TLSHT147F423BAF6C70C5553ED31782428840BCF31BBD87287291B5B9DD1C2F1AE0F6D466A68
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
FileSize5512124
MD5C300B6A622E3E70B72373E196A71AE51
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
PackageVersion1.44-9-1
SHA-10E17D939F22C3DB6A41069624595EF4204B80D4B
SHA-2561BA3FC9194A6409F75539F371E21FBF8C55A8543C1B363371F5D19FE637C475E