Package: quantiseqr 1.15.0
Federico Marini
quantiseqr: Quantification of the Tumor Immune contexture from RNA-seq data
This package provides a streamlined workflow for the quanTIseq method, developed to perform the quantification of the Tumor Immune contexture from RNA-seq data. The quantification is performed against the TIL10 signature (dissecting the contributions of ten immune cell types), carefully crafted from a collection of human RNA-seq samples. The TIL10 signature has been extensively validated using simulated, flow cytometry, and immunohistochemistry data.
Authors:
quantiseqr_1.15.0.tar.gz
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quantiseqr.pdf |quantiseqr.html✨
quantiseqr/json (API)
NEWS
| # Install 'quantiseqr' in R: |
| install.packages('quantiseqr', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- dataset_racle - An exemplary dataset with samples from four patients with metastatic melanoma
- ti_quant_sim1700mixtures - QuanTIseq output for the simulation data of 1700 mixtures for RNA-seq data
On BioConductor:quantiseqr-1.15.0(bioc 3.21)quantiseqr-1.14.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
geneexpressionsoftwaretranscriptiontranscriptomicssequencingmicroarrayvisualizationannotationimmunooncologyfeatureextractionclassificationstatisticalmethodexperimenthubsoftwareflowcytometry
Last updated 23 days agofrom:d4608cde78. Checks:OK: 1 NOTE: 4 WARNING: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | NOTE | Oct 31 2024 |
| R-4.5-linux | NOTE | Oct 31 2024 |
| R-4.4-win | NOTE | Oct 31 2024 |
| R-4.4-mac | WARNING | Oct 31 2024 |
| R-4.3-win | NOTE | Oct 31 2024 |
| R-4.3-mac | WARNING | Oct 31 2024 |
Exports:eset_to_matrixextract_ti_from_seget_densitiesquantiplotrun_quantiseqse_to_matrix
Dependencies:abindaskpassBiobaseBiocGenericsclicolorspacecpp11crayoncurlDelayedArraydplyrfansifarvergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehttrIRangesisobandjsonlitelabelinglatticelifecyclelimSolvelpSolvemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpillarpkgconfigpreprocessCorepurrrquadprogR6RColorBrewerrlangS4ArraysS4VectorsscalesSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Check the signature matrix | check_signature |
| An exemplary dataset with samples from four patients with metastatic melanoma | dataset_racle |
| Solve Least Squares with Equality and Inequality Constraints (LSEI) problem | DClsei |
| Perform robust regression | DCrr |
| Convert a 'Biobase::ExpressionSet' to a gene-expression matrix. | eset_to_matrix |
| Extract tumor immune quantifications | extract_ti_from_se |
| Format the mixture matrix before deconvolution | fixMixture |
| Scale deconvoluted cell fractions to cell densities | get_densities |
| Perform quantile normalization of expression data | makeQN |
| Rename gene symbols before deconvolution | mapGenes |
| Plot the information on the tumor immune contexture | quantiplot |
| Run quanTIseq deconvolution | quanTIseq |
| Helper functions for quanTIseq | quantiseq_helper |
| quantiseqr package | quantiseqr-pkg |
| Run the quanTIseq algorithm | run_quantiseq |
| SummarizedExperiment to matrix | se_to_matrix |
| quanTIseq output for the simulation data of 1700 mixtures for RNA-seq data | ti_quant_sim1700mixtures |
