Package: spatialLIBD 1.25.3

Leonardo Collado-Torres

spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data

Inspect interactively the spatially-resolved transcriptomics data from the 10x Genomics Visium platform as well as data from the Maynard, Collado-Torres et al, Nature Neuroscience, 2021 project analyzed by Lieber Institute for Brain Development (LIBD) researchers and collaborators.

Authors:Leonardo Collado-Torres [aut, cre], Kristen R. Maynard [ctb], Andrew E. Jaffe [ctb], Brenda Pardo [ctb], Abby Spangler [ctb], Jesús Vélez Santiago [ctb], Lukas M. Weber [ctb], Louise Huuki-Myers [ctb], Nicholas Eagles [ctb]

spatialLIBD_1.25.3.tar.gz
spatialLIBD_1.25.3.tar.gz(r-4.7-any)spatialLIBD_1.25.3.tar.gz(r-4.6-any)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
spatialLIBD/json (API)

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

Bug tracker:https://github.com/lieberinstitute/spatiallibd/issues

Datasets:

On BioConductor:spatialLIBD-1.25.3(data/experiment 3.24)spatialLIBD-1.24.0(data/experiment 3.23)

homo_sapiens_dataexperimenthubsequencingdatasinglecelldataexpressiondatatissuepackagetypedataspatialdata10xgenomicsbioconductorgolemshinyspatial-transcriptomicsspatialexperimentspatiallibdvisiumdatapkg

11.18 score 114 stars 3 packages 1.0k scripts 48 exports 184 dependencies

Last updated from:f63819319a. Checks:1 ERROR, 2 NOTE, 1 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR216
linux-develNOTE911
source / vignettesOK557
linux-releaseNOTE846

Exports:add_imagesadd_keyadd_qc_metricsadd10xVisiumAnalysisannotate_registered_clusterscheck_modeling_resultscheck_scecheck_sce_layercheck_specluster_exportcluster_importenough_ramfetch_dataframe_limitsgene_set_enrichmentgene_set_enrichment_plotgeom_spatialget_colorsimg_editimg_updateimg_update_alllayer_boxplotlayer_stat_corlayer_stat_cor_plotlocate_imagesread10xVisiumAnalysisread10xVisiumWrapperregistration_block_corregistration_modelregistration_pseudobulkregistration_stats_anovaregistration_stats_enrichmentregistration_stats_pairwiseregistration_wrapperrun_appsce_to_spesig_genes_extractsig_genes_extract_allsort_clustersvis_clusvis_clus_cvis_clus_pvis_genevis_gene_cvis_gene_pvis_grid_clusvis_grid_genevis_image

Dependencies:abindAnnotationDbiAnnotationHubaskpassassortheadattemptbase64encbeachmatbeeswarmbenchmarkmebenchmarkmeDataBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIObiocmakeBiocManagerBiocNeighborsBiocParallelBiocSingularBiocVersionBiostringsbitbit64bitopsblobbslibcachemcigarillocirclizecliclueclustercodetoolscolorspacecommonmarkComplexHeatmapconfigcowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArraydigestdir.expirydoParalleldplyrdqrngDTedgeRevaluateExperimentHubfarverfastmapfilelockFNNfontawesomeforeachformatRfsfutile.loggerfutile.optionsgenericsGenomicAlignmentsGenomicRangesGetoptLongggbeeswarmggplot2ggrepelGlobalOptionsgluegolemgridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrhttr2IRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalocfitmagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisemimeopensslotelpaletteerpheatmappillarpkgconfigplotlypngprismaticpromisespurrrR6rappdirsRColorBrewerRcppRcppAnnoyRcppEigenRcppMLRcppProgressRCurlrematch2restfulrRhtslibRigraphlibrjsonrlangrmarkdownRsamtoolsRSpectraRSQLiterstudioapirsvdrtracklayerRtsneS4ArraysS4VectorsS7sassScaledMatrixscalesscaterscrapperscuttleSeqinfosessioninfoshapeshinyshinyWidgetsSingleCellExperimentsitmosnowsourcetoolsSparseArraySpatialExperimentstatmodstringistringrSummarizedExperimentsystibbletidyrtidyselecttinytexutf8uwotvctrsviporviridisviridisLitewithrxfunXMLxtableXVectoryaml

Introduction to spatialLIBD
Welcome | Study design | Shiny website mirrors | Basics | Install spatialLIBD | Required knowledge | Asking for help | Citing spatialLIBD | Overview | Human DLPFC Visium dataset | Data specifics | Downloading the data with spatialLIBD | Interactively explore the spatialLIBD data | spatialLIBD functions | Spot-level clusters and discrete variables | Spot-level genes and continuous variables | Extract significant genes | Visualize modeling results | Correlation of layer-level statistics | Gene set enrichment | Re-shaping your data to our structure | SpatialExperiment support | Using spatialLIBD with your own data | Expected characteristics of the data | Generating our data (legacy) | More spatially-resolved LIBD datasets | spatialDLPFC | Visium_SPG_AD | LIBD data outside spatialLIBD | locus-c | Reproducibility | Bibliography
Rendered fromspatialLIBD.Rmdusingknitr::rmarkdown

Last update: 2024-12-13
Started: 2020-02-19

Guide to Multi-Gene Plots
Plotting One Gene | Plotting Multiple Genes | Averaging Z-scores | Summarizing with PCA | Plotting Sparsity of Expression | With more marker genes | Visualizing non-gene continuous variables | Reproducibility | Bibliography
Rendered frommulti_gene_plots.Rmdusingknitr::rmarkdown

Last update: 2024-12-13
Started: 2024-02-21

Guide to Spatial Registration
What is Spatial Registration? | Overview of the Spatial Registration method | How to run Spatial Registration with spatialLIBD tools | Introduction. | Important Notes | Required knowledge | Citing spatialLIBD | Setup | Install spatialLIBD | Load required packages | Download Data | Spatial Reference | Query Data: snRNA-seq | Get Enrichment statistics for snRNA-seq data | Extract Enrichment t-statistics | Correlate statsics with Layer Reference | Explore Results | Create Heatmap of Correlations | Annotate Cell Types by Top Correlation | Plot Annotated Cell Types | Reproducibility | Bibliography
Rendered fromguide_to_spatial_registration.Rmdusingknitr::rmarkdown

Last update: 2024-12-12
Started: 2023-04-28

Using spatialLIBD with 10x Genomics public datasets
Basics | Install spatialLIBD | Required knowledge | Citing spatialLIBD | Download data from 10x Genomics | Load packages | Download spaceranger output files | Modify spe for spatialLIBD | Add gene annotation information | From 10x | From Gencode | Enable a friendlier gene search | Filter the spe object | Check object | Explore the data | Run the interactive website | Wrapper functions | Publishing your web application | Limitations | Memory | Response speeds | Image resolution | Customization | Reproducibility | Bibliography
Rendered fromTenX_data_download.Rmdusingknitr::rmarkdown

Last update: 2022-03-30
Started: 2021-03-31

Readme and manuals

Help Manual

Help pageTopics
Add non-standard images with the same dimensions as current onesadd_images
Create a unique spot identifieradd_key
Quality Control for Spatial Dataadd_qc_metrics
Add analysis data from a 10x Genomics Visium experiment to a SPE objectadd10xVisiumAnalysis
Annotated spatially-registered clustersannotate_registered_clusters
Check input modeling_resultscheck_modeling_results
Check input scecheck_sce
Check input sce_layercheck_sce_layer
Check input specheck_spe
Export a column with cluster resultscluster_export
Import cluster resultscluster_import
Determine if you have enough RAM memoryenough_ram
Download the Human DLPFC Visium data from LIBDfetch_data
Identify the image limitsframe_limits
Evaluate the enrichment for a list of gene setsgene_set_enrichment
Plot the gene set enrichment results with ComplexHeatmapgene_set_enrichment_plot
A ggplot2 layer for visualizing the Visium histologygeom_spatial
Obtain the colors for a set of cluster namesget_colors
Edit a background imageimg_edit
Update the image for one sampleimg_update
Update the images for all samplesimg_update_all
Layer-level (group-level) boxplotslayer_boxplot
Layer modeling correlation of statisticslayer_stat_cor
Visualize the correlation of layer modeling t-statistics with ComplexHeatmaplayer_stat_cor_plot
Vector of LIBD layer colorslibd_layer_colors
Locate image fileslocate_images
Load analysis data from a 10x Genomics Visium experimentread10xVisiumAnalysis
Load data from a 10x Genomics Visium experiment and make it spatialLIBD-readyread10xVisiumWrapper
Spatial registration: block correlationregistration_block_cor
Spatial registration: modelregistration_model
Spatial registration: pseudobulkregistration_pseudobulk
Spatial registration: compute ANOVA statisticsregistration_stats_anova
Spatial registration: compute enrichment statisticsregistration_stats_enrichment
Spatial registration: compute pairwise statisticsregistration_stats_pairwise
Spatial registration: wrapper functionregistration_wrapper
Run the spatialLIBD Shiny Applicationrun_app
Convert a SCE object to a SPE onesce_to_spe
Extract significant genessig_genes_extract
Extract significant genes for all modeling resultssig_genes_extract_all
Sort clusters by frequencysort_clusters
Cell cluster t-statistics from Tran et altstats_Human_DLPFC_snRNAseq_Nguyen_topLayer
Sample spatial cluster visualizationvis_clus
Sample spatial cluster visualization workhorse function for Xenium data with centroid based spatailCoordsvis_clus_c
Sample spatial cluster visualization workhorse function for Visium data with pixel based spatailCoords aligned to images.vis_clus_p
Sample spatial gene visualizationvis_gene
Sample spatial gene visualization workhorse function for Xenium data with centroid based spatailCoordsvis_gene_c
Sample spatial gene visualization workhorse functionvis_gene_p
Sample spatial cluster visualization gridvis_grid_clus
Sample spatial gene visualization gridvis_grid_gene
Sample image visualizationvis_image