Package: Linnorm 2.37.0
Linnorm: Linear model and normality based normalization and transformation method (Linnorm)
Linnorm is an algorithm for normalizing and transforming RNA-seq, single cell RNA-seq, ChIP-seq count data or any large scale count data. It has been independently reviewed by Tian et al. on Nature Methods (https://doi.org/10.1038/s41592-019-0425-8). Linnorm can work with raw count, CPM, RPKM, FPKM and TPM.
Authors:
Linnorm_2.37.0.tar.gz
Linnorm_2.37.0.zip(r-4.7)Linnorm_2.37.0.zip(r-4.6)Linnorm_2.37.0.zip(r-4.5)
Linnorm_2.37.0.tgz(r-4.6-x86_64)Linnorm_2.37.0.tgz(r-4.6-arm64)Linnorm_2.37.0.tgz(r-4.5-x86_64)Linnorm_2.37.0.tgz(r-4.5-arm64)
Linnorm_2.37.0.tar.gz(r-4.7-arm64)Linnorm_2.37.0.tar.gz(r-4.7-x86_64)Linnorm_2.37.0.tar.gz(r-4.6-arm64)Linnorm_2.37.0.tar.gz(r-4.6-x86_64)
Linnorm_2.37.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
Linnorm/json (API)
NEWS
| # Install 'Linnorm' in R: |
| install.packages('Linnorm', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:Linnorm-2.37.0(bioc 3.24)Linnorm-2.36.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
immunooncologysequencingchipseqrnaseqdifferentialexpressiongeneexpressiongeneticsnormalizationsoftwaretranscriptionbatcheffectpeakdetectionclusteringnetworksinglecellcpp
Last updated from:88a4885237. Checks:12 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 177 | ||
| linux-devel-arm64 | NOTE | 395 | ||
| linux-devel-x86_64 | NOTE | 342 | ||
| source / vignettes | OK | 367 | ||
| linux-release-arm64 | NOTE | 335 | ||
| linux-release-x86_64 | NOTE | 410 | ||
| macos-release-arm64 | NOTE | 211 | ||
| macos-release-x86_64 | NOTE | 711 | ||
| macos-oldrel-arm64 | NOTE | 234 | ||
| macos-oldrel-x86_64 | NOTE | 605 | ||
| windows-devel | NOTE | 859 | ||
| windows-release | NOTE | 432 | ||
| windows-oldrel | NOTE | 734 | ||
| wasm-release | OK | 135 |
Exports:LinearRegressionLinearRegressionFPLinnormLinnorm.CorLinnorm.DataImputLinnorm.HClustLinnorm.HVarLinnorm.limmaLinnorm.NormLinnorm.PCALinnorm.SGenesLinnorm.tSNERnaXSim
Dependencies:amapapclusterclasscliclustercpp11DEoptimRdiptestellipsefarverfastclusterflexmixfpcgdataggdendroggplot2gluegmodelsgtablegtoolsigraphisobandkernlablabelinglatticelifecyclelimmamagrittrMASSMatrixmclustmgcvmodeltoolsnlmennetpermutepkgconfigprabclusR6RColorBrewerRcppRcppArmadillorlangrobustbaseRtsneS7scalesstatmodvctrsveganviridisLitewithrzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| scRNA-seq data from Islam et al. 2011 | Islam2011 |
| Partial RNA-seq data from TCGA LIHC (Liver Hepatocellular Carcinoma) | LIHC |
| One Pass Linear Regression. | LinearRegression |
| One Pass Linear Regression with fixed point. | LinearRegressionFP |
| Linnorm Normalizing Transformation Function | Linnorm |
| Linnorm-gene correlation network analysis. | Linnorm.Cor |
| Linnorm Data Imputation Function. (In development) | Linnorm.DataImput |
| Linnorm-hierarchical clustering analysis. | Linnorm.HClust |
| Linnorm-Hvar pipeline for highly variable gene discovery. | Linnorm.HVar |
| Linnorm-limma pipeline for Differentially Expression Analysis | Linnorm.limma |
| Linnorm Normalization Function | Linnorm.Norm |
| Linnorm-PCA Clustering pipeline for subpopulation Analysis | Linnorm.PCA |
| Linnorm model stable gene selection tool. | Linnorm.SGenes |
| Linnorm t-SNE Clustering pipeline for subpopulation Analysis | Linnorm.tSNE |
| This function simulates an RNA-seq dataset based on a given distribution. | RnaXSim |
| Partial RNA-seq data from SEQC/MAQC-III Sample A | SEQC |
