Result for 0627F4ED5AA319BBE93EA2AA466C2A152D382496

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/help/qtl.rdb
FileSize775819
MD54FB96939F0FE7F6AC8D6BB94F5D79686
SHA-10627F4ED5AA319BBE93EA2AA466C2A152D382496
SHA-256D85EFC41E25D526E1E9BEE4401DB4179C59581D477D0385CA4788723AF9D16E4
SSDEEP12288:HhR2LWTCbuYmzfujYzInOhipC4Co/gvKKGQkcY963nxPEKHNlNyDF8hjacXFulR4:HrD+lmz2jYEOh4CsGKnQkcYU3p/lNy50
TLSHT11CF4238BDF0D48E41B1D232BD1A4D25DD66EA5F6BC2A52F52B83E00B30696C7B4C197C
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