Package: CellProgramMapper 1.0.0

CellProgramMapper: Map Single Cells to Reference Gene Expression Programs

Maps single-cell RNA sequencing data to reference gene expression programs (GEPs) using non-negative matrix factorization. Enables cell type annotation and state characterization by projecting query cells onto pre-built or custom reference programs. Includes tools for building consensus references from multiple datasets. Features C++ accelerated NNLS solvers and built-in machine learning models for cell type prediction.

Authors:Zaoqu Liu [aut, cre]

CellProgramMapper_1.0.0.tar.gz
CellProgramMapper_1.0.0.zip(r-4.7)CellProgramMapper_1.0.0.zip(r-4.6)CellProgramMapper_1.0.0.zip(r-4.5)
CellProgramMapper_1.0.0.tgz(r-4.6-x86_64)CellProgramMapper_1.0.0.tgz(r-4.6-arm64)CellProgramMapper_1.0.0.tgz(r-4.5-x86_64)CellProgramMapper_1.0.0.tgz(r-4.5-arm64)
CellProgramMapper_1.0.0.tar.gz(r-4.7-arm64)CellProgramMapper_1.0.0.tar.gz(r-4.7-x86_64)CellProgramMapper_1.0.0.tar.gz(r-4.6-arm64)CellProgramMapper_1.0.0.tar.gz(r-4.6-x86_64)
CellProgramMapper_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CellProgramMapper/json (API)

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

Bug tracker:https://github.com/zaoqu-liu/cellprogrammapper/issues

Pkgdown/docs site:https://zaoqu-liu.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

3.48 score 1 stars 12 scripts 17 exports 16 dependencies

Last updated from:aa7f0ba8d0 (on main). Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK204
linux-devel-x86_64OK223
source / vignettesOK345
linux-release-arm64OK197
linux-release-x86_64OK230
macos-release-arm64OK106
macos-release-x86_64OK328
macos-oldrel-arm64OK118
macos-oldrel-x86_64OK258
windows-develOK206
windows-releaseOK174
windows-oldrelOK179
wasm-releaseOK213

Exports:add_results_to_seuratavailable_referencesBuildConsensusReferenceCellProgramMappercompute_scorescreate_score_datacreate_score_definitiondownload_referenceget_lineage_probabilitiesget_scoresget_usagelist_builtin_modelsload_countsload_referenceread_df_from_npzread_npzsave_results

Dependencies:codetoolscurldata.tabledigestfuturefuture.applyglobalsjsonlitelatticelistenvMatrixparallellyrappdirsRcppRcppArmadilloyaml

Mathematical Framework and Algorithm
Introduction | Problem Formulation | Non-Negative Matrix Factorization (NMF) | Projection Problem | Cell-wise Decomposition | NNLS Problem | Standard Form | KKT Conditions | Data Preprocessing | Scaling | Why Not Center? | Usage Normalization | Computational Complexity | Visualization of the Algorithm | Example: Geometric Interpretation | Summary | References | Session Info
Rendered fromalgorithm.Rmdusingknitr::rmarkdown

Last update: 2026-01-26
Started: 2026-01-26

NNLS Solver Implementation Details
Overview | The NNLS Problem | Active Set Method (Lawson-Hanson) | Algorithm Description | Convergence Properties | Implementation | Coordinate Descent Method | Advantages | Comparison | Benchmark | Choosing a Solver | Numerical Considerations | Tolerance Parameter | Maximum Iterations | Division by Zero Protection | Session Info
Rendered fromnnls-solver.Rmdusingknitr::rmarkdown

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Started: 2026-01-26

Quick Start Guide
Introduction | Installation | Quick Example | Available References | Input Formats | Working with Results | Access Usage Matrix | Access Scores | Save Results | Demonstration with Simulated Data | Performance Tips | Next Steps | Session Info
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Started: 2026-01-26

Building Custom References
Introduction | Reference Format | File Format | Method 1: From cNMF Results | Running cNMF | Loading cNMF Results | Method 2: Building Consensus Reference | Method 3: Manual Construction | From Known Gene Signatures | From Expression Data | Validating Custom References | Quality Checks | Visualize Reference | Saving References | As TSV File | With Metadata | Using Custom References | Best Practices | Reference Construction | Gene Overlap | Recommendations | Troubleshooting | Low Gene Overlap | All-Zero Usage | High Reconstruction Error | Session Info
Rendered fromcustom-reference.Rmdusingknitr::rmarkdown

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Started: 2026-01-26

Visualization Guide
Introduction | Load Example Data | Simulated Example Data | Usage Matrix Heatmap | Program Activity on UMAP | Score Distributions | Violin Plots | Ridge Plot | Program Correlation Analysis | Correlation Heatmap | Network Visualization | Publication-Ready Figures | Combined Panel Figure | Saving High-Resolution Figures | Integration with Seurat | Tips for Effective Visualization | Session Info
Rendered fromvisualization.Rmdusingknitr::rmarkdown

Last update: 2026-01-26
Started: 2026-01-26