Result for 09E4635B4638B2740244F8461D3D1E03F9E81FCB

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/R/qtl.rdx
FileSize5570
MD5530D0D358161F1EBAEA80B2F004A719F
SHA-109E4635B4638B2740244F8461D3D1E03F9E81FCB
SHA-25631453AB032E0ABABC44EF117B2187A3FF3AC2DA4F439CFBF52D74A1C39AEE44E
SSDEEP96:FIkZR0n3W5twuIh53QM+h4WQytpf6hx6z8U9dSV3Jsatn7VO8NBhKp2p12eIS1Dm:mkZRdH2BQ994hgz8UzSd/tZOY1pLw5/
TLSHT18CB17E19495AB0EB74E71EFE4F8801996D3C4C9C43639E585E0BE313257892A8B6E9E0
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
FileSize5022486
MD539EE8384121F9B92017413545BB75057
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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamer-cran-qtl
PackageSectiongnu-r
PackageVersion1.37-11-1
SHA-17406E4D5A17C1F06FE9D44EA3752F48A64AA0D1C
SHA-256D8D780F0FC201FAB7B7EBD04ACB064A504DC0134F3190AF7310CBBC6598081EE