Result for 040ECF2F9D0EF3D46C91A986D993D97215937A54

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/R/qtl.rdb
FileSize1777565
MD535BB4650C01B0D90B63BAB83507C39A7
SHA-1040ECF2F9D0EF3D46C91A986D993D97215937A54
SHA-256A50A5EA0964EF8498A504DBB42392B232BB0CE7A81F85E388B07E7B2B05B1476
SSDEEP49152:GLJMSaApAVFie9WHUb/DR6U/cEnMbC0p0US9oy:GLRS7WHULDeEncC2Xm
TLSHT19885331FFA6947A89878CF80CF640A95D44D264FE0C6AC3A63C0CD93D6697BF51B1C29
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
FileSize5509276
MD5746B6EBD3654BABF1630B60EB3E89EA3
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
PackageVersion1.47-9-1
SHA-161A7F299095D30700F3F099D6FB1F1D651BC3FA8
SHA-256CC0D44FBEF4A6014BA2818C8127621AB3750DDCC6972D8516222E6DA7775AC9D