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'))

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

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

On CRAN:

Conda:

2.70 score 427 downloads 6 exports 29 dependencies

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

TargetResultLatest binary
Doc / VignettesOKMar 10 2025
R-4.5-linuxOKMar 10 2025
R-4.4-linuxOKMar 10 2025

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

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandkernlablabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

QuESTr

Takahiko Koizumi

Rendered fromQuESTr.Rmdusingknitr::rmarkdownon Mar 10 2025.

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