The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

JUMP: Replicability Analysis of High-Throughput Experiments

Implementing a computationally scalable false discovery rate control procedure for replicability analysis based on maximum of p-values. Please cite the manuscript corresponding to this package [Lyu, P. et al., (2023), <https://www.biorxiv.org/content/10.1101/2023.02.13.528417v2>].

Version: 1.0.1
Depends: R (≥ 4.1.2), Rcpp, splines, stats
LinkingTo: Rcpp, RcppArmadillo
Published: 2023-05-24
Author: Pengfei Lyu [aut, ctb], Yan Li [aut, cre, cph], Xiaoquan Wen [aut], Hongyuan Cao [aut, ctb]
Maintainer: Yan Li <yanli_ at jlu.edu.cn>
License: GPL-3
NeedsCompilation: yes
CRAN checks: JUMP results

Documentation:

Reference manual: JUMP.pdf

Downloads:

Package source: JUMP_1.0.1.tar.gz
Windows binaries: r-devel: JUMP_1.0.1.zip, r-release: JUMP_1.0.1.zip, r-oldrel: JUMP_1.0.1.zip
macOS binaries: r-release (arm64): JUMP_1.0.1.tgz, r-oldrel (arm64): JUMP_1.0.1.tgz, r-release (x86_64): JUMP_1.0.1.tgz, r-oldrel (x86_64): JUMP_1.0.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=JUMP to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.