Result for 0821E35902D4F7D5AA8855CDC8E6F198C5BBF385

Query result

Key Value
FileName./usr/lib/R/site-library/qtl/R/qtl.rdb
FileSize454913
MD520582FE5EEF499D244D1428D6C4B83FB
SHA-10821E35902D4F7D5AA8855CDC8E6F198C5BBF385
SHA-25635E3DE39BBA144092F7BA7A274A6FCFCAF4C86D1F5B2ECF025648DD29A7C42C2
SSDEEP12288:8YavgHwUQ27KiyFca9JBkZr7mLRM8ptaGExWCxr1Jv:8RUQUKiyB0Ge8p4Gurbv
TLSHT1EEA423AB1C76C84DFE304189BC7B0B7CA37AD3B91ED458995297C13AC98D1219F2C369
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
FileSize5022684
MD5994F37C529B630C00FF8CE7C540C28B5
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-10765EF32CCED8DFFBE9D15F85B426C96ACC089CF
SHA-25656C37B4EE4F9A10B11445CCD5433525A616C972DEC9552E2E31A1AB067B3D457