Package: STRIDER 1.0.0

STRIDER: Spatial Transcriptomics Deconvolution and Integration in R

STRIDER (Spatial Transcriptomics deconvolutIon and integration in R) provides comprehensive tools for analyzing spatial transcriptomics data. The package implements topic modeling based deconvolution using Latent Dirichlet Allocation (LDA) to decompose spatial spots into cell type proportions. It also provides multi-sample integration using Fused Gromov-Wasserstein (FGW) optimal transport, spatial clustering with neighborhood awareness, and visualization functions. STRIDER is designed to work seamlessly with Seurat objects (v4 and v5) and supports various input formats including 10X Genomics HDF5 files.

Authors:Zaoqu Liu [aut, cre]

STRIDER_1.0.0.tar.gz
STRIDER_1.0.0.zip(r-4.7)STRIDER_1.0.0.zip(r-4.6)STRIDER_1.0.0.zip(r-4.5)
STRIDER_1.0.0.tgz(r-4.6-x86_64)STRIDER_1.0.0.tgz(r-4.6-arm64)STRIDER_1.0.0.tgz(r-4.5-x86_64)STRIDER_1.0.0.tgz(r-4.5-arm64)
STRIDER_1.0.0.tar.gz(r-4.7-arm64)STRIDER_1.0.0.tar.gz(r-4.7-x86_64)STRIDER_1.0.0.tar.gz(r-4.6-arm64)STRIDER_1.0.0.tar.gz(r-4.6-x86_64)
STRIDER_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
STRIDER/json (API)

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

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

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

On CRAN:

Conda:

openblascppopenmp

1.81 score 13 scripts 71 exports 24 dependencies

Last updated from:8fbfecb48f (on main). Checks:11 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING166
linux-devel-x86_64WARNING185
source / vignettesOK211
linux-release-arm64WARNING164
linux-release-x86_64WARNING184
macos-release-arm64WARNING103
macos-release-x86_64WARNING222
macos-oldrel-arm64WARNING106
macos-oldrel-x86_64WARNING208
windows-develWARNING182
windows-releaseWARNING151
windows-oldrelWARNING169
wasm-releaseOK136

Exports:align_samplesas_seuratbenchmark_stridercalculate_celltype_topic_bayescalculate_coherencecalculate_neighbor_fractionscalculate_nmicalculate_qc_metricscalculate_topic_celltypecenter_coordscenter_points_cppcluster_compositioncluster_in_topic_spacecluster_silhouettecombine_plotscompute_distance_matrixcompute_kl_divergencecompute_rotation_svd_cppcreate_mapping_graphcreate_strider_objectdeconvolveeuclidean_distance_cppevaluate_model_predictionevaluate_topic_rangefilter_cellsfilter_genesfind_cluster_markersfind_markersfind_markers_scanpyfind_neighborsfind_variable_genesfrom_seuratfused_gromov_wasserstein_cppget_default_colorsget_extended_colorsget_mapped_celltypesget_shared_genesintegrate_samplesintegration_qualitykl_divergence_matrix_cppmap_spots_to_cellsnormalize_countsplot_celltype_heatmapplot_clusterplot_deconvplot_deconv_pieplot_deconv_scatterplot_integrationplot_mappingplot_model_selectionplot_topic_heatmapplot_validationpreprocess_scpreprocess_stread_10x_h5read_celltype_annotationsread_count_matrixread_gene_listread_spatial_coordsrun_stridersave_plotscale_dataselect_best_modelspatial_clustertrain_ldatrain_modeltransfer_labelstransform_ldavalidate_striderwrite_10x_h5write_results

Dependencies:clicpp11data.tablefarverggplot2gluegridExtragtableisobandlabelinglatticelifecycleMatrixR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Align Two Samples Using FGWalign_samples
Convert STRIDER Object to Seuratas_seurat
Benchmark STRIDER Against Known Ground Truthbenchmark_strider
Calculate Bayesian Celltype-Topic Matrixcalculate_celltype_topic_bayes
Calculate LDA Coherence Scorecalculate_coherence
Calculate Neighbor Average Fractionscalculate_neighbor_fractions
Calculate Normalized Mutual Informationcalculate_nmi
Calculate Quality Control Metricscalculate_qc_metrics
Calculate Topic-Celltype Association Matrixcalculate_topic_celltype
Center Coordinatescenter_coords
Center Points by Weighted Meancenter_points_cpp
Calculate Cluster Statisticscluster_composition
Perform K-Means Clustering on Topic Spacecluster_in_topic_space
Calculate Silhouette Score for Clusteringcluster_silhouette
Spatial Clustering Functions for STRIDERclustering
Combine Multiple Plotscombine_plots
Compute Spatial Distance Matrixcompute_distance_matrix
Compute KL Divergence Matrixcompute_kl_divergence
Compute Optimal Rotation via SVDcompute_rotation_svd_cpp
Create Spot-Cell Neighborhood Graphcreate_mapping_graph
Create STRIDER Objectcreate_strider_object
Data Input/Output Functions for STRIDERdata_io
Cell Type Deconvolution Functions for STRIDERdeconvolve
Compute Euclidean Distance Matrixeuclidean_distance_cpp
Evaluate Model Using Cell Type Predictionevaluate_model_prediction
Evaluate Multiple Topic Numbersevaluate_topic_range
Filter Cells/Spotsfilter_cells
Filter Genesfilter_genes
Find Enriched Cell Types per Clusterfind_cluster_markers
Find Marker Genes for Each Cell Typefind_markers
Find Marker Genes (scanpy-style workflow)find_markers_scanpy
Find Spatial Neighborsfind_neighbors
Find Highly Variable Genesfind_variable_genes
Create STRIDER Object from Seuratfrom_seurat
Fused Gromov-Wasserstein Distancefused_gromov_wasserstein_cpp
Default Color Paletteget_default_colors
Generate Color Paletteget_extended_colors
Get Mapped Cell Informationget_mapped_celltypes
Get Shared Genes Between Datasetsget_shared_genes
Integrate Multiple Spatial Transcriptomics Samplesintegrate_samples
Multi-Sample Integration Functions for STRIDERintegration
Calculate Integration Quality Metricsintegration_quality
Compute KL Divergence Matrixkl_divergence_matrix_cpp
LDA Topic Model for STRIDERlda_model
Map Spatial Spots to Similar Single Cellsmap_spots_to_cells
Spot-to-Cell Mapping Functions for STRIDERmapping
Marker Gene Identification for STRIDERmarker_find
Model Evaluation Functions for STRIDERmodel_evaluate
Normalize Countsnormalize_counts
Visualization Functions for STRIDERplot
Plot Cell Type Composition Heatmapplot_celltype_heatmap
Plot Cluster Resultsplot_cluster
Plot Deconvolution Resultsplot_deconv
Scatter Pie Plot for Deconvolutionplot_deconv_pie
Scatter Plot for Deconvolutionplot_deconv_scatter
Plot Integration Resultsplot_integration
Visualize Spot-Cell Mappingplot_mapping
Plot Model Selection Resultsplot_model_selection
Plot Topic Distribution Heatmapplot_topic_heatmap
Compare Cell Type Proportionsplot_validation
Preprocessing Functions for STRIDERpreprocess
Preprocess Single-Cell Datapreprocess_sc
Preprocess Spatial Datapreprocess_st
Print STRIDER Objectprint.STRIDER
Print Benchmark Resultsprint.strider_benchmark
Print Method for Integration Resultprint.strider_integration
Print Method for LDA Modelprint.strider_lda
Print Validation Reportprint.strider_validation
Read 10X Genomics HDF5 Fileread_10x_h5
Read Cell Type Annotationsread_celltype_annotations
Read Count Matrix from Text Fileread_count_matrix
Read Gene Listread_gene_list
Read Spatial Coordinatesread_spatial_coords
Run STRIDER Deconvolution Pipelinerun_strider
Save Plot to Filesave_plot
Scale Data by Standard Deviationscale_data
Select Best Modelselect_best_model
Spatial Clustering Based on Cell Type Compositionspatial_cluster
Summary of STRIDER Objectsummary.STRIDER
Train LDA Topic Modeltrain_lda
Train LDA Model (Convenience Wrapper)train_model
Transfer Labels from Single Cells to Spotstransfer_labels
Apply LDA Model to New Datatransform_lda
Scientific Validation Functions for STRIDERvalidate
Validate STRIDER Results Against Referencevalidate_strider
Write 10X Genomics HDF5 Filewrite_10x_h5
Write Results to Filewrite_results