## ----message=FALSE, warning=FALSE, include=FALSE------------------------------ knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE) ## ----eval=FALSE--------------------------------------------------------------- # if (!require("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("standR") ## ----eval=FALSE--------------------------------------------------------------- # devtools::install_github("DavisLaboratory/standR") ## ----message = FALSE, warning = FALSE----------------------------------------- library(standR) library(SpatialExperiment) library(limma) library(ExperimentHub) ## ----message = FALSE, warning = FALSE----------------------------------------- eh <- ExperimentHub() query(eh, "standR") countFile <- eh[["EH7364"]] sampleAnnoFile <- eh[["EH7365"]] featureAnnoFile <- eh[["EH7366"]] spe <- readGeoMx(countFile, sampleAnnoFile, featureAnnoFile = featureAnnoFile, rmNegProbe = TRUE) ## ----------------------------------------------------------------------------- colData(spe)$regions <- paste0(colData(spe)$region,"_",colData(spe)$SegmentLabel) |> (\(.) gsub("_Geometric Segment","",.))() |> paste0("_",colData(spe)$pathology) |> (\(.) gsub("_NA","_ns",.))() library(ggalluvial) plotSampleInfo(spe, column2plot = c("SlideName","disease_status","regions")) ## ----------------------------------------------------------------------------- spe <- addPerROIQC(spe, rm_genes = TRUE) ## ----------------------------------------------------------------------------- plotGeneQC(spe, ordannots = "regions", col = regions, point_size = 2) ## ----------------------------------------------------------------------------- plotROIQC(spe, y_threshold = 50000, col = SlideName) ## ----------------------------------------------------------------------------- spe <- spe[,rownames(colData(spe))[colData(spe)$lib_size > 50000]] ## ----------------------------------------------------------------------------- plotRLExpr(spe, ordannots = "SlideName", assay = 2, col = SlideName) ## ----------------------------------------------------------------------------- drawPCA(spe, assay = 2, col = SlideName, shape = regions) ## ----------------------------------------------------------------------------- colData(spe)$biology <- paste0(colData(spe)$disease_status, "_", colData(spe)$regions) spe_tmm <- geomxNorm(spe, method = "TMM") ## ----------------------------------------------------------------------------- spe <- findNCGs(spe, batch_name = "SlideName", top_n = 500) metadata(spe) |> names() ## ----------------------------------------------------------------------------- spe_ruv <- geomxBatchCorrection(spe, factors = "biology", NCGs = metadata(spe)$NCGs, k = 5) ## ----------------------------------------------------------------------------- plotPairPCA(spe_ruv, assay = 2, color = disease_status, shape = regions, title = "RUV4") ## ----------------------------------------------------------------------------- plotRLExpr(spe_ruv, assay = 2, color = SlideName) + ggtitle("RUV4") ## ----------------------------------------------------------------------------- sessionInfo()