How to Install and Uninstall r-bioc-multtest Package on Kali Linux

Last updated: May 21,2024

1. Install "r-bioc-multtest" package

Please follow the instructions below to install r-bioc-multtest on Kali Linux

$ sudo apt update $ sudo apt install r-bioc-multtest

2. Uninstall "r-bioc-multtest" package

This guide let you learn how to uninstall r-bioc-multtest on Kali Linux:

$ sudo apt remove r-bioc-multtest $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-bioc-multtest package on Kali Linux

Package: r-bioc-multtest
Version: 2.58.0-1
Installed-Size: 1054
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, r-api-bioc-3.18, r-bioc-biocgenerics, r-bioc-biobase, r-cran-survival, r-cran-mass, libc6 (>= 2.29)
Suggests: r-cran-snow
Size: 837860
SHA256: fd20fadf72f0578494d73acf6e71e82e01eaf0ca661756f50049a3ab84ee146c
SHA1: c837ebc1ce32666a45f013702e875f41ec153345
MD5sum: 5c62b6fefef532ab8cf20a17be8d4bb1
Description: Bioconductor resampling-based multiple hypothesis testing
Non-parametric bootstrap and permutation resampling-based multiple
testing procedures (including empirical Bayes methods) for controlling
the family-wise error rate (FWER), generalized family-wise error rate
(gFWER), tail probability of the proportion of false positives (TPPFP),
and false discovery rate (FDR). Several choices of bootstrap-based null
distribution are implemented (centered, centered and scaled,
quantile-transformed). Single-step and step-wise methods are available.
Tests based on a variety of t- and F-statistics (including t-statistics
based on regression parameters from linear and survival models as well
as those based on correlation parameters) are included. When probing
hypotheses with t-statistics, users may also select a potentially faster
null distribution which is multivariate normal with mean zero and
variance covariance matrix derived from the vector influence function.
Results are reported in terms of adjusted p-values, confidence regions
and test statistic cutoffs. The procedures are directly applicable to
identifying differentially expressed genes in DNA microarray
experiments.
Description-md5:
Homepage: https://bioconductor.org/packages/multtest/
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-bioc-multtest/r-bioc-multtest_2.58.0-1_amd64.deb