Package: QuESTr 0.1.1

Takahiko Koizumi

QuESTr: Constructing Quantitative Environment Sensor using Transcriptomes

A method for prediction of environmental conditions based on transcriptome data linked with the environmental gradients. This package provides functions to overview gene-environment relationships, to construct the prediction model, and to predict environmental conditions where the transcriptomes were generated. This package can quest for candidate genes for the model construction even in non-model organisms' transcriptomes without any genetic information.

Authors:Takahiko Koizumi, Kenta Suzuki, Yasunori Ichihashi

QuESTr_0.1.1.tar.gz
QuESTr_0.1.1.tar.gz(r-4.5-noble)QuESTr_0.1.1.tar.gz(r-4.4-noble)
QuESTr_0.1.1.tgz(r-4.4-emscripten)QuESTr_0.1.1.tgz(r-4.3-emscripten)
QuESTr.pdf |QuESTr.html✨
QuESTr/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/takakoizumi/questr/issues

Datasets:
  • Pinus - Transcriptomes of Pinus roots under a Temperature Gradient

2.70 score 4 scripts 341 downloads 6 exports 29 dependencies

Last updated 3 years agofrom:dbeb2497dc. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 10 2024
R-4.5-linuxOKDec 10 2024

Exports:q.cleanq.optq.pcaq.rankq.sortquest

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandkernlablabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

QuESTr

Takahiko Koizumi

Rendered fromQuESTr.Rmdusingknitr::rmarkdownon Dec 10 2024.

Last update: 2022-02-15
Started: 2022-02-15