Package: QRscore 1.5.0

Fanding Zhou

QRscore: Quantile Rank Score

In genomics, differential analysis enables the discovery of groups of genes implicating important biological processes such as cell differentiation and aging. Non-parametric tests of differential gene expression usually detect shifts in centrality (such as mean or median), and therefore suffer from diminished power against alternative hypotheses characterized by shifts in spread (such as variance). This package provides a flexible family of non-parametric two-sample tests and K-sample tests, which is based on theoretical work around non-parametric tests, spacing statistics and local asymptotic normality (Erdmann-Pham et al., 2022+ [arXiv:2008.06664v2]; Erdmann-Pham, 2023+ [arXiv:2209.14235v2]).

Authors:Fanding Zhou [cre, aut], Alan Aw [aut], Dan Erdmann-Pham [aut], Jonathan Fischer [aut], Xurui Chen [ctb]

QRscore_1.5.0.tar.gz
QRscore_1.5.0.zip(r-4.7)QRscore_1.5.0.zip(r-4.6)QRscore_1.5.0.zip(r-4.5)
QRscore_1.5.0.tgz(r-4.6-any)QRscore_1.5.0.tgz(r-4.5-any)
QRscore_1.5.0.tar.gz(r-4.7-any)QRscore_1.5.0.tar.gz(r-4.6-any)
QRscore_1.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
QRscore/json (API)

# Install 'QRscore' in R:

install.packages('QRscore', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/songlab-cal/qrscore/issues

Datasets:

example_dataset - Example Dataset for MOCHIS DEG Analysis
example_dataset_raw_3000_genes - Example Dataset for MOCHIS DEG Analysis with Raw Counts

On BioConductor:QRscore-1.5.0(bioc 3.24)QRscore-1.4.0(bioc 3.23)

statisticalmethod differentialexpression geneexpression structuralgenomics genetarget

3.30 score 1 stars 3 scripts 10 exports 31 dependencies

Last updated from:8de552f1de. Checks:1 NOTE, 7 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	183
linux-devel-x86_64	WARNING	257
source / vignettes	OK	250
linux-release-x86_64	WARNING	276
macos-release-arm64	WARNING	191
macos-oldrel-arm64	WARNING	193
windows-devel	WARNING	251
windows-release	WARNING	287
windows-oldrel	WARNING	288
wasm-release	OK	188

Exports:computeweight_disp computeweight_mean getCompositionPValue QRscore_Flex QRscore_ZINB QRscore_ZINB_nSamples QRscoreGenetest QRscoreTest rank_x rzinbinom

Dependencies:arrangements assertthat BH BiocParallel cli codetools cpp11 dplyr formatR futile.logger futile.options generics glue gmp hitandrun lambda.r lifecycle magrittr MASS pillar pkgconfig pscl R6 rcdd rlang snow tibble tidyselect utf8 vctrs withr

Help page	Topics
Compute weights for dispersion shift analysis	computeweight_disp
Compute weights for mean shift analysis	computeweight_mean
Example Dataset for MOCHIS DEG Analysis	example_dataset
Example Dataset for MOCHIS DEG Analysis with Raw Counts	example_dataset_raw_3000_genes
Approximate p-value by Resampling Integer Compositions	getCompositionPValue
QRscore: Nonparametric Quantile Rank Score Tests for Distributional Shifts in Gene Expression	QRscore-package QRscore
Flexible Non-Parametric One- and Two-Sample Tests (Native R version)	QRscore_Flex
Non-Parametric Two-Sample Tests Designed for Testing Differences in Mean or Dispersion Parameters in (Zero-Inflated) Negative Binomial Distributions.	QRscore_ZINB
Multi-Sample Nonparametric Test for Mean or Dispersion Differences in (Zero-Inflated) Negative Binomial Distributions.	QRscore_ZINB_nSamples
Perform Differential Expression Analysis using QRscore	QRscoreGenetest
QRscore Test	QRscoreTest
Retrieve indices of x_i's after merging \boldsymbol{x} and \boldsymbol{y} in ascending order.	rank_x
Generate random samples from a zero-inflated negative binomial distribution	rzinbinom

Package: QRscore 1.5.0

QRscore: Quantile Rank Score

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