Result for 01B5A077AE38455D3BDC9A300120F5A121252875

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/R/qtl.rdb
FileSize430661
MD59C636D43BBB0CD534C69E86DDD944129
SHA-101B5A077AE38455D3BDC9A300120F5A121252875
SHA-2569BEDE73C1C6BEC0B51DD6FCB657CB052842C9CD9901FDDCB2C2D8D9FDDEA7A60
SSDEEP6144:a1PR9Qt1gFg3cgyIZ9pdQhsKJCJ9HahMeXsX5Hj/MebpDXPcG3NGBuE5Q1i0MjIk:63Q3QgII/WsK6ahtXqdj/MelIIGtQHMT
TLSHT124942343420E4D5B0C96970559F10B84A35237F7ADA6E853228BE634F8B980BDFE6DDC
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
FileSize4383888
MD57570CA289B425FFBB2A6CAA8DADA00D2
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 Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
PackageNamer-cran-qtl
PackageSectiongnu-r
PackageVersion1.33-7-1
SHA-15229C87058A483B0EBCACBE45B6C7F2876E09CBC
SHA-25624AF65F308F7D912DA6974A3D3F004634376C8E9635C2D9AC89D514711326FCC