Result for 0015ABEE88560AF71145E26FEAA4B6635DEC8485

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/help/paths.rds
FileSize1724
MD5D03CD82481953755D98112FD51679E97
SHA-10015ABEE88560AF71145E26FEAA4B6635DEC8485
SHA-256C4B1D8A262A86447EC179D6750700C89C96BA269069AA0145B911C56BC9EB03D
SSDEEP48:XO2ekl8biP+nISKejTVdSqzBmZhwEt5AEQ/B:+2H9FSKe3fSAmZhTc
TLSHT15B313A8634D86D6A4A8BD51F1C30A7FE813D10774D9CAA2B95FC33BB0CCC369804AE05
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
FileSize4188734
MD5483E8DCC3AFCF99115D14707BD6F1AB7
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
PackageVersion1.40-8-1
SHA-145F7A7FE5514F63D741E6C5EA3DAEB629C63CB44
SHA-256CB22B3DD46ECB8F69B51A2AA6AC02CE875FC38C33FC025743B1DE554AFF46CC8