Package: SRTsim 0.99.7

Jiaqiang Zhu

SRTsim: Simulator for Spatially Resolved Transcriptomics

An independent, reproducible, and flexible Spatially Resolved Transcriptomics (SRT) simulation framework that can be used to facilitate the development of SRT analytical methods for a wide variety of SRT-specific analyses. It utilizes spatial localization information to simulate SRT expression count data in a reproducible and scalable fashion. Two major simulation schemes are implemented in 'SRTsim': reference-based and reference-free.

Authors:Jiaqiang Zhu [aut, ctb, cre], Lulu Shang [aut], Xiang Zhou [aut]

SRTsim_0.99.7.tar.gz
SRTsim_0.99.7.tar.gz(r-4.5-noble)SRTsim_0.99.7.tar.gz(r-4.4-noble)
SRTsim_0.99.7.tgz(r-4.4-emscripten)SRTsim_0.99.7.tgz(r-4.3-emscripten)
SRTsim.pdf |SRTsim.html✨
SRTsim/json (API)

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

Peer review:

Datasets:
  • exampleLIBD - Data used for creating vignettes
  • toyData - A toyExample to showcase reference-based simulations
  • toyShiny - A toyExample to showcase reference-free simulations

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 9 scripts 188 downloads 24 exports 148 dependencies

Last updated 3 months agofrom:8625bd6ace. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linuxOKNov 20 2024

Exports:compareSRTconvert_gridcreateSRTEstParammetaParamrefcolDatarefCountsrefrowDatareGenCountshinyShiny2SRTsimcolDatasimCountssimNewLocssimrowDatasrtsim_cci_freesrtsim_cci_refsrtsim_countsrtsim_count_affinesrtsim_fitsrtsim_newlocsSRTsim_shinysubsetSRTvisualize_genevisualize_metrics

Dependencies:abindaskpassbackportsbase64encbezierBiocGenericsbootbroombslibcachemcarcarDataclassclassIntclicodetoolscolorRampscolorspacecommonmarkconcavemancorrplotcowplotcpp11crayoncrosstalkcurldashboardthemesdata.tableDBIdeldirDerivdigestdoBydoParalleldplyrDTe1071evaluatefansifarverfastmapFNNfontawesomeforeachFormulafsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallifecyclelme4magickmagrittrMASSMatrixMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminqamodelrMorphomunsellnlmenloptrnnetnumDerivopensslpbkrtestpdistpillarpkgconfigplotlypolyclippolynompromisesproxypurrrquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenrglrlangrmarkdownrstatixRvcgs2S4VectorssassscalessfshinyshinyBSshinydashboardsourcetoolsspSparseMspatstat.dataspatstat.geomspatstat.randomspatstat.univarspatstat.utilsstringistringrsurvivalsystibbletidyrtidyselecttinytexunitsutf8V8vctrsviridisviridisLitewithrwkxfunxtableyaml

Introduction to SRTsim

Jiaqiang Zhu

Rendered fromSRTsim.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2024-08-22
Started: 2022-06-24

Readme and manuals

Help Manual

Help pageTopics
Summarize metrics for reference data and synthetic datacompareSRT
Convert continuous coordinate into integer, essential for BayesSpace to determine the neighborhood infoconvert_grid
Create simSRT objectcreateSRT
Access Model Fitting ParametersEstParam
Data used for creating vignettesexampleLIBD
fitting data with poisson through optim functionfit_pos_optim
Extracted summarized metrics for reference data and synthetic dataget_metrics_pd
Summarize gene-wise summary metricsget_stats_gene
Summarize location-wise summary metricsget_stats_loc
Access User-Specified ParametersmetaParam
Access reference colDatarefcolData
Access reference count matrixrefCounts
Access reference rowDatarefrowData
ReSimulate Count Data with Parameters Specification from ShinyreGenCountshiny
Create a SRTsim object from reference-free shinyoutputShiny2SRT
Access synthetic colDatasimcolData
Access synthetic count matrixsimCounts
Fit the marginal distributions for single genesimNewLocs
Access synthetic rowDatasimrowData
Generate Data with Cell-Cell Interaction Under Reference-Free Modesrtsim_cci_free
Generate Data with Cell-Cell Interaction Under Reference-Based Modesrtsim_cci_ref
Generate Data with Estimated Parameterssrtsim_count
Generate Data with Estimated Parameters For A New Designed Patternsrtsim_count_affine
Fit the marginal distributions for each row of a count matrixsrtsim_fit
Fit the marginal distributions for each row of a count matrixsrtsim_newlocs
Run the SRTsim Shiny ApplicationSRTsim_shiny
Subset SRT object based on domain labels of interestsubsetSRT
A toyExample to showcase reference-based simulationstoyData
A toyExample to showcase reference-free simulationstoyShiny
Visualize expression pattern for the gene of interest in reference data and synthetic datavisualize_gene
Visualize summarized metrics for reference data and synthetic datavisualize_metrics