Package: snpAIMeR 2.1.1

snpAIMeR: Assess the Diagnostic Power of Genomic Marker Combinations

Population genetics package for designing diagnostic panels. Candidate markers, marker combinations, and different panel sizes are assessed for how well they can predict the source population of known samples. Requires a genotype file of candidate markers in STRUCTURE format. Methods for population cross-validation are described in Jombart (2008) <doi:10.1093/bioinformatics/btn129>.

Authors:Kim Vertacnik [cre, aut], Oksana Vernygora [aut], Julian Dupuis [aut]

snpAIMeR_2.1.1.tar.gz
snpAIMeR_2.1.1.zip(r-4.5)snpAIMeR_2.1.1.zip(r-4.4)snpAIMeR_2.1.1.zip(r-4.3)
snpAIMeR_2.1.1.tgz(r-4.4-any)snpAIMeR_2.1.1.tgz(r-4.3-any)
snpAIMeR_2.1.1.tar.gz(r-4.5-noble)snpAIMeR_2.1.1.tar.gz(r-4.4-noble)
snpAIMeR_2.1.1.tgz(r-4.4-emscripten)snpAIMeR_2.1.1.tgz(r-4.3-emscripten)
snpAIMeR.pdf |snpAIMeR.html
snpAIMeR/json (API)
NEWS

# Install 'snpAIMeR' in R:
install.packages('snpAIMeR', repos = c('https://kvertacnik.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/oksanave/snpaimer/issues

On CRAN:

2.00 score 1 scripts 168 downloads 1 exports 89 dependencies

Last updated 9 months agofrom:7049c037e3. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

Exports:snpAIMeR

Dependencies:ade4adegenetapebase64encbitbit64bootbslibcachemclicliprclustercodetoolscolorspacecommonmarkcpp11crayondigestdoParalleldplyrfansifarverfastmapfontawesomeforcatsforeachfsgenericsggplot2gluegtablehmshtmltoolshttpuvigraphisobanditeratorsjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepermutepillarpixmappkgconfigplyrprettyunitsprogresspromisespurrrR6rappdirsRColorBrewerRcppRcppArmadilloreadrreshape2rlangsassscalessegmentedseqinrshinysourcetoolsspstringistringrtibbletidyrtidyselecttzdbutf8vctrsveganviridisLitevroomwithrxtableyaml