Introduction | Getting started | Some use cases for quantiseqr | Use case 1: Metastatic melanoma patients (Racle et al 2017) | Use case 2: PBMCs from GSE107572 (Finotello et al 2019) | Use case 3: Expression changes in melanoma patients on vs. pre kinase-inhibitor treatment - GSE75299 (Song et al 2017) | Use case 4: Running on simulated data for validation | FAQs | Session Info | References
Package: quantiseqr 1.21.1
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_1.21.1.tar.gz
quantiseqr_1.21.1.zip(r-4.7)quantiseqr_1.21.1.zip(r-4.6)quantiseqr_1.21.1.zip(r-4.5)
quantiseqr_1.21.1.tgz(r-4.6-any)quantiseqr_1.21.1.tgz(r-4.5-any)
quantiseqr_1.21.1.tar.gz(r-4.7-any)quantiseqr_1.21.1.tar.gz(r-4.6-any)
quantiseqr_1.21.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
quantiseqr/json (API)
| # Install 'quantiseqr' in R: |
| install.packages('quantiseqr', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- 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-1.21.0(bioc 3.24)quantiseqr-1.20.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
geneexpressionsoftwaretranscriptiontranscriptomicssequencingmicroarrayvisualizationannotationimmunooncologyfeatureextractionclassificationstatisticalmethodexperimenthubsoftwareflowcytometry
Last updated from:066ab68f52. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 255 | ||
| linux-devel-x86_64 | NOTE | 420 | ||
| source / vignettes | OK | 340 | ||
| linux-release-x86_64 | NOTE | 425 | ||
| macos-release-arm64 | NOTE | 284 | ||
| macos-oldrel-arm64 | NOTE | 221 | ||
| windows-devel | NOTE | 286 | ||
| windows-release | NOTE | 254 | ||
| windows-oldrel | NOTE | 274 | ||
| wasm-release | OK | 195 |
Exports:eset_to_matrixextract_ti_from_seget_densitiesquantiplotrun_quantiseqse_to_matrix
Dependencies:abindBiobaseBiocGenericsclicpp11DelayedArraydplyrfarvergenericsGenomicRangesggplot2gluegtableIRangesisobandlabelinglatticelifecyclelimSolvelpSolvemagrittrMASSMatrixMatrixGenericsmatrixStatspillarpkgconfigpreprocessCorepurrrquadprogR6RColorBrewerrlangS4ArraysS4VectorsS7scalesSeqinfoSparseArraystringistringrSummarizedExperimenttibbletidyrtidyselectutf8vctrsviridisLitewithrXVector
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 |
| 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 |
