Package: standR 1.11.1

Ning Liu

standR: Spatial transcriptome analyses of Nanostring's DSP data in R

standR is an user-friendly R package providing functions to assist conducting good-practice analysis of Nanostring's GeoMX DSP data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. standR allows data inspection, quality control, normalization, batch correction and evaluation with informative visualizations.

Authors:Ning Liu [aut, cre], Dharmesh D Bhuva [aut], Ahmed Mohamed [aut]

standR_1.11.1.tar.gz
standR_1.11.1.zip(r-4.5)standR_1.11.1.zip(r-4.4)standR_1.11.1.zip(r-4.3)
standR_1.11.1.tgz(r-4.4-any)standR_1.11.1.tgz(r-4.3-any)
standR_1.11.1.tar.gz(r-4.5-noble)standR_1.11.1.tar.gz(r-4.4-noble)
standR_1.11.1.tgz(r-4.4-emscripten)standR_1.11.1.tgz(r-4.3-emscripten)
standR.pdf |standR.html✨
standR/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/davislaboratory/standr/issues

Datasets:

    On BioConductor:standR-1.11.1(bioc 3.21)standR-1.10.0(bioc 3.20)

    spatialtranscriptomicsgeneexpressiondifferentialexpressionqualitycontrolnormalizationexperimenthubsoftware

    7.36 score 18 stars 40 scripts 268 downloads 21 exports 141 dependencies

    Last updated 18 days agofrom:0dbb86e18c. Checks:OK: 7. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKDec 04 2024
    R-4.5-winOKDec 04 2024
    R-4.5-linuxOKDec 04 2024
    R-4.4-winOKDec 04 2024
    R-4.4-macOKDec 04 2024
    R-4.3-winOKDec 04 2024
    R-4.3-macOKDec 04 2024

    Exports:addPerROIQCcomputeClusterEvalStatsdrawPCAfindBestKfindNCGsgeomxBatchCorrectiongeomxNormplotClusterEvalStatsplotDRplotGeneQCplotMDSplotPairPCAplotPCAbiplotplotRLExprplotROIQCplotSampleInfoplotScreePCAprepareSpatialDeconreadGeoMxreadGeoMxFromDGEspe2dge

    Dependencies:abindAnnotationDbiaroma.lightaskpassBHBiobaseBiocFileCacheBiocGenericsBiocIOBiocManagerBiocParallelbiomaRtBiostringsbitbit64bitopsblobcachemclicliprcodetoolscolorspacecpp11crayoncurlDBIdbplyrDelayedArraydeldirdigestdplyrEDASeqedgeRfansifarverfastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicFeaturesGenomicRangesggalluvialggplot2gluegridExtragtablehmshttrhttr2hwriterinterpIRangesisobandjpegjsonliteKEGGRESTlabelinglambda.rlatticelatticeExtralazyevallifecyclelimmalocfitmagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmclustcompmemoisemgcvmimemunsellnlmeopensslpatchworkpillarpkgconfigplogrpngprettyunitsprogresspurrrpwalignR.methodsS3R.ooR.utilsR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRCurlRdpackreadrrestfulrRhtslibrjsonrlangRsamtoolsRSQLitertracklayerruvRUVSeqS4ArraysS4VectorsscalesShortReadSingleCellExperimentsnowSparseArraySpatialExperimentstatmodstringistringrSummarizedExperimentsystibbletidyrtidyselecttzdbUCSC.utilsutf8vctrsviridisLitevroomwithrXMLxml2XVectoryamlzlibbioc

    A quick start guide to the standR package

    Ning Liu, Dharmesh Bhuva, Ahmed Mohamed, Chin Wee Tan, Melissa Davis

    Rendered fromQuick_start.Rmdusingknitr::rmarkdownon Dec 04 2024.

    Last update: 2023-03-29
    Started: 2023-02-23

    Readme and manuals

    Help Manual

    Help pageTopics
    Add QC statistics to the Spatial Experiment objectaddPerROIQC
    Calculate statistics for evaluating batch correctioncomputeClusterEvalStats
    Compute and plot the results of a PCA analysis on gene expression datadrawPCA drawPCA,DGEList-method drawPCA,ExpressionSet-method drawPCA,SingleCellExperiment-method drawPCA,SpatialExperiment-method drawPCA,SummarizedExperiment-method
    Testing multiple K for RUV4 batch correction to find the best K.findBestK
    Get negative control genes from each batch of the datafindNCGs
    Batch correction for GeoMX datageomxBatchCorrection
    Perform normalization to GeoMX datageomxNorm
    Compare and evaluate different batch corrected data with plotting.plotClusterEvalStats
    Compute and plot the results of any dimension reduction methods on gene expression dataplotDR plotDR,SingleCellExperiment-method plotDR,SpatialExperiment-method
    Plot gene-wise QC plotplotGeneQC
    Compute and plot the results of a MDS analysis on gene expression dataplotMDS plotMDS,DGEList-method plotMDS,ExpressionSet-method plotMDS,SingleCellExperiment-method plotMDS,SpatialExperiment-method plotMDS,SummarizedExperiment-method
    Plot pair-wise PCA plots for multiple dimensionsplotPairPCA
    Plot PCA bi plotplotPCAbiplot
    Compute and plot relative log expression (RLE) values of gene expression dataplotRLExpr plotRLExpr,DGEList-method plotRLExpr,ExpressionSet-method plotRLExpr,SummarizedExperiment-method
    Plot Sample-wise QC plotplotROIQC
    Plot the user-defined meta data using alluvium plotplotSampleInfo
    Plot the PCA scree plot.plotScreePCA
    Preparing the inputs for SpatialDecon for doing deconvolution on spatial dataprepareSpatialDecon
    Import GeoMX DSP data into a saptial experiment object from file pathsreadGeoMx
    Import GeoMX DSP data into a spatial experiment object from DGEList objectreadGeoMxFromDGE
    Transfer SpatialExperiment object into DGEList object for DE analysisspe2dge