Package: QuantNorm 1.0.5

QuantNorm: Mitigating the Adverse Impact of Batch Effects in Sample Pattern Detection

Modifies the distance matrix obtained from data with batch effects, so as to improve the performance of sample pattern detection, such as clustering, dimension reduction, and construction of networks between subjects. The method has been published in Bioinformatics (Fei et al, 2018, <doi:10.1093/bioinformatics/bty117>). Also available on 'GitHub' <https://github.com/tengfei-emory/QuantNorm>.

Authors:Teng Fei, Tianwei Yu

QuantNorm_1.0.5.tar.gz
QuantNorm_1.0.5.zip(r-4.5)QuantNorm_1.0.5.zip(r-4.4)QuantNorm_1.0.5.zip(r-4.3)
QuantNorm_1.0.5.tgz(r-4.4-any)QuantNorm_1.0.5.tgz(r-4.3-any)
QuantNorm_1.0.5.tar.gz(r-4.5-noble)QuantNorm_1.0.5.tar.gz(r-4.4-noble)
QuantNorm_1.0.5.tgz(r-4.4-emscripten)QuantNorm_1.0.5.tgz(r-4.3-emscripten)
QuantNorm.pdf |QuantNorm.html
QuantNorm/json (API)

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

Peer review:

Bug tracker:https://github.com/tengfei-emory/quantnorm/issues

Datasets:
  • ENCODE - Normalized ENCODE raw counts data for both human and mouse.
  • brain - Brain RNA-Seq data for both human and mouse.

On CRAN:

batch-effects

2 exports 9 stars 1.58 score 0 dependencies 1 mentions 9 scripts 143 downloads

Last updated 5 years agofrom:ddb0076bff. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 26 2024
R-4.5-winNOTEAug 26 2024
R-4.5-linuxNOTEAug 26 2024
R-4.4-winNOTEAug 26 2024
R-4.4-macNOTEAug 26 2024
R-4.3-winNOTEAug 26 2024
R-4.3-macNOTEAug 26 2024

Exports:connection.matrixQuantNorm

Dependencies: