Introduction | Package Installation and other requirements | Spatial Transcriptomics Data | Reference-free Deconvolution | Cell-type Annotation via annotated single-cell reference | Cell-type Annotation via known marker genes | Results and visualization | Figure 4A: Proportion of different cell types in the tissue. | Figure 4C: Localization of cell types with the dominant cell type in each spot | Figure 4D: Gene expression of Epithelial marker genes across spots | Figure 4E: Proportion of Epithelial cells across spots | Figure 5A: Proportion of different cell types in different spots | Figure 5D: Spots with 1 dominant cell type i.e., proportion > 0.5 | Figure 5E: Co-localized spots for Epithelial cells | Figure 6C: Concordance between expression profiles of found genes obtained from RETROFIT and scRNA-seq data | Session information
Package: retrofit 1.13.0
Adam Park
retrofit: RETROFIT: Reference-free deconvolution of cell mixtures in spatial transcriptomics
RETROFIT is a Bayesian non-negative matrix factorization framework to decompose cell type mixtures in ST data without using external single-cell expression references. RETROFIT outperforms existing reference-based methods in estimating cell type proportions and reconstructing gene expressions in simulations with varying spot size and sample heterogeneity, irrespective of the quality or availability of the single-cell reference. RETROFIT recapitulates known cell-type localization patterns in a Slide-seq dataset of mouse cerebellum without using any single-cell data.
Authors:
retrofit_1.13.0.tar.gz
retrofit_1.13.0.zip(r-4.7)retrofit_1.13.0.zip(r-4.6)retrofit_1.13.0.zip(r-4.5)
retrofit_1.13.0.tgz(r-4.6-x86_64)retrofit_1.13.0.tgz(r-4.6-arm64)retrofit_1.13.0.tgz(r-4.5-x86_64)retrofit_1.13.0.tgz(r-4.5-arm64)
retrofit_1.13.0.tar.gz(r-4.7-arm64)retrofit_1.13.0.tar.gz(r-4.7-x86_64)retrofit_1.13.0.tar.gz(r-4.6-arm64)retrofit_1.13.0.tar.gz(r-4.6-x86_64)
retrofit_1.13.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
retrofit/json (API)
| # Install 'retrofit' in R: |
| install.packages('retrofit', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/qunhualilab/retrofit/issues
Datasets:
- testSimulationData - Simulation data
- vignetteColonData - Colon vignette
- vignetteSimulationData - Simulation vignette
On BioConductor:retrofit-1.13.0(bioc 3.24)retrofit-1.12.0(bioc 3.23)
transcriptomicsvisualizationrnaseqbayesianspatialsoftwaregeneexpressiondimensionreductionfeatureextractionsinglecellcpp
Last updated from:ca4aee1f6b. Checks:1 WARNING, 11 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 186 | ||
| linux-devel-arm64 | NOTE | 146 | ||
| linux-devel-x86_64 | NOTE | 151 | ||
| source / vignettes | OK | 207 | ||
| linux-release-arm64 | NOTE | 146 | ||
| linux-release-x86_64 | NOTE | 182 | ||
| macos-release-arm64 | NOTE | 89 | ||
| macos-release-x86_64 | NOTE | 264 | ||
| macos-oldrel-arm64 | NOTE | 115 | ||
| macos-oldrel-x86_64 | NOTE | 237 | ||
| windows-devel | NOTE | 117 | ||
| windows-release | NOTE | 127 | ||
| windows-oldrel | NOTE | 142 | ||
| wasm-release | OK | 140 |
Exports:annotateWithCorrelationsannotateWithMarkersdecomposeretrofit
Dependencies:Rcpp
Retrofit Colon Vignette
Last update: 2023-02-27
Started: 2022-12-24
Retrofit Simulation Vignette
Introduction | Package Installation | Spatial Transcriptomics Data | Deconvolution | Cell-type Annotation | Deconvolution and annotation in one step (Optional) | Results | Session information
Last update: 2023-02-27
Started: 2022-12-12
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| RETROFIT matching algorithm | annotateWithCorrelations |
| RETROFIT matching algorithm | annotateWithMarkers |
| RETROFIT decomposition algorithm | decompose |
| RETROFIT | retrofit |
| simulation data | testSimulationData |
| colon vignette | vignetteColonData |
| simulation vignette | vignetteSimulationData |
