Package: scPAS 1.0.4

scPAS: Single-Cell Phenotype-Associated Subpopulation Identifier

Identifies phenotype-associated cell subpopulations from single-cell RNA-seq data by integrating bulk RNA-seq data with phenotype information. This package uses network-regularized sparse regression to quantify the strength of association between each cell and a phenotype (e.g., disease stage, tumor metastasis, treatment response, survival outcomes). Compatible with both Seurat v4 (4.0.0+) and Seurat v5 (5.0.0+). The method supports Gaussian (continuous), binomial (binary), and Cox (survival) regression families. Full cross-platform compatibility (Windows, macOS, Linux).

Authors:Aimin Xie [aut], Zaoqu Liu [aut, cre]

scPAS_1.0.4.tar.gz
scPAS_1.0.4.zip(r-4.7)scPAS_1.0.4.zip(r-4.6)scPAS_1.0.4.zip(r-4.5)
scPAS_1.0.4.tgz(r-4.6-x86_64)scPAS_1.0.4.tgz(r-4.6-arm64)scPAS_1.0.4.tgz(r-4.5-x86_64)scPAS_1.0.4.tgz(r-4.5-arm64)
scPAS_1.0.4.tar.gz(r-4.7-arm64)scPAS_1.0.4.tar.gz(r-4.7-x86_64)scPAS_1.0.4.tar.gz(r-4.6-arm64)scPAS_1.0.4.tar.gz(r-4.6-x86_64)
scPAS_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
scPAS/json (API)

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

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

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

3.78 score 10 scripts 7 exports 143 dependencies

Last updated from:8f4f190d3e. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK264
linux-devel-x86_64OK344
source / vignettesOK390
linux-release-arm64OK259
linux-release-x86_64OK342
macos-release-arm64OK270
macos-release-x86_64OK432
macos-oldrel-arm64OK252
macos-oldrel-x86_64OK434
windows-develOK240
windows-releaseOK221
windows-oldrelOK229
wasm-releaseOK204

Exports:imputationimputation_ALRAimputation_KNNrun_SeuratscPASscPAS.predictionsparse.cor

Dependencies:abindaskpassbase64encBHbitopsbslibcachemcaToolscliclustercodetoolscommonmarkcowplotcpp11crosstalkcurldata.tabledeldirdigestdotCall64dplyrdqrngevaluatefarverfastDummiesfastmapfitdistrplusFNNfontawesomefsfuturefuture.applygenericsggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallifecyclelistenvlmtestmagrittrMASSMatrixmatrixStatsmemoisemimeminiUInlmeopensslotelparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclippreprocessCoreprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLreshape2reticulaterlangrmarkdownROCRrprojrootRSpectraRtsneS7sassscalesscattermoresctransformSeuratSeuratObjectshinysitmosourcetoolsspspamspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsystensortibbletidyrtidyselecttinytexutf8uwotvctrsviridisLitewithrxfunxtableyamlzoo

Case Study: Binary Classification
Introduction | Biological Question | Clinical Context | Setup | Simulated Immunotherapy Data | Single-Cell Data: Pre-treatment Tumor Biopsies | Bulk Data: Pre-treatment with Response Annotation | Visualize Response Distribution | Run scPAS with Binomial Family | Visualize Results | UMAP Overview | Cell Type Response Association | Detailed Violin Plot | Stacked Bar Plot | Biological Interpretation | Responder-Associated Populations (scPAS+) | Non-Responder-Associated Populations (scPAS-) | Predictive Signature | Extract Response Signature | Signature Visualization | Publication Figure | Clinical Application | Predict Response for New Patients | Key Takeaways | Session Information

Last update: 2026-01-23
Started: 2026-01-23

Case Study: Cancer Survival Analysis
Introduction | Biological Question | Analysis Overview | Setup | Simulated Cancer Data | Single-Cell Data: Tumor Microenvironment | Bulk Data: TCGA-like Cohort with Survival | Visualize Survival Data | Run scPAS with Cox Regression | Visualize Results | UMAP Overview | Cell Type Enrichment | Violin Plot by Cell Type | Biological Interpretation | Key Findings | Publication Figure | Model Application to New Data | Key Takeaways | Session Information

Last update: 2026-01-23
Started: 2026-01-23

scPAS : Single-Cell Phenotype-Associated Subpopulation identifier
Introduction | Installation | Apply scPAS with Cox regression | Load data | Prepare the scRNA-seq data | Prepare the bulk data and phenotype | Run scPAS without imputation | Run scPAS with imputation | Apply the trained model to independent bulk data | Apply the trained model to spatial transcriptomics data | Information about the current R session

Last update: 2026-01-23
Started: 2025-12-29

Algorithm and Methodology
Overview | Mathematical Framework | Problem Formulation | Network-Regularized Sparse Regression | Loss Functions by Phenotype Type | Gaussian Family (Continuous) | Binomial Family (Binary) | Cox Family (Survival) | Gene Network Construction | Shared Nearest Neighbor (SNN) Network | Risk Score Calculation | Per-Cell Risk Score | Normalized Risk Score | Statistical Significance Testing | Permutation Test | FDR Correction | Cell Classification | Implementation Details | Sparse Matrix Operations | Parallel Computing | References | Session Information

Last update: 2026-01-23
Started: 2026-01-23

Quick Start Guide
Introduction | Key Features | Package Installation | Quick Example | Load Required Packages | Simulate Example Data | Preprocess Single-Cell Data | Run scPAS Analysis | Examine Results | Basic Visualization | Output Structure | Three Phenotype Types | 1. Continuous Phenotype (Gaussian) | 2. Binary Phenotype (Binomial) | 3. Survival Phenotype (Cox) | Next Steps | Session Information

Last update: 2026-01-23
Started: 2026-01-23

Visualization Gallery
Introduction | Setup and Simulated Data | Create Simulated scPAS Result | Basic UMAP Plots | Cell Type Overview | Risk Score Visualization | Cell Classification | Combined Multi-Panel Plot | Cell Type Enrichment Analysis | Proportion Bar Plot | Enrichment Heatmap | Volcano-Style Plot | Violin Plots | Risk Score by Cell Type | Split Violin by Classification | Box Plots with Statistical Tests | Density Plots | Pie Chart Summary | Publication-Ready Figure | Saving Plots | Session Information

Last update: 2026-01-23
Started: 2026-01-23