## ----style, echo = FALSE, results = 'asis'------------------------------------ BiocStyle::markdown() ## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, eval = TRUE, message = FALSE, warning=FALSE, error = TRUE) ## ----eval=FALSE--------------------------------------------------------------- # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # BiocManager::install("granulator") ## ----eval=TRUE---------------------------------------------------------------- library(granulator) ## ----results='hide'----------------------------------------------------------- # load datasets for deconvolution of PBMC RNA-seq data load_ABIS() ## ----------------------------------------------------------------------------- # print TPM values in bulk RNA-seq bulkRNAseq_ABIS[1:5, 1:5] ## ----------------------------------------------------------------------------- # print TPM values in reference profile matrix sigMatrix_ABIS_S0[1:5, 1:5] ## ----------------------------------------------------------------------------- # print measured cell type proportions (percentages) groundTruth_ABIS[1:5, 1:5] ## ----------------------------------------------------------------------------- # create list if multiple signature matrices to test simultaneously sigList = list( ABIS_S0 = sigMatrix_ABIS_S0, ABIS_S1 = sigMatrix_ABIS_S1, ABIS_S2 = sigMatrix_ABIS_S2, ABIS_S3 = sigMatrix_ABIS_S3) ## ----fig.retina = 1----------------------------------------------------------- # plot signature matrix similarity matrices plot_similarity(sigMatrix=sigList) ## ----results='hide'----------------------------------------------------------- # deconvolute input data using all available methods by default decon <- deconvolute(m = bulkRNAseq_ABIS, sigMatrix = sigList) ## ----------------------------------------------------------------------------- # print cell type proportions for svr model on ABIS_S0 reference profile decon$proportions$svr_ABIS_S0[1:5, 1:5] ## ----fig.retina = 1----------------------------------------------------------- # plot cell type proportions for svr model on ABIS_S0 reference profile plot_proportions(deconvoluted = decon, method = 'svr', signature = 'ABIS_S0') ## ----fig.retina = 1----------------------------------------------------------- # plot cell type proportions plot_deconvolute(deconvoluted = decon, scale = TRUE, labels = FALSE) ## ----------------------------------------------------------------------------- # benchmark methods by correlating estimated to measured cell type proportions bench <- benchmark(deconvoluted = decon, ground_truth = groundTruth_ABIS) ## ----------------------------------------------------------------------------- # print metrics head(bench$summary) ## ----------------------------------------------------------------------------- # print metrics head(bench$rank) ## ----fig.retina = 1----------------------------------------------------------- # plot regression for svr model on ABIS_S0 reference profile plot_regress(benchmarked = bench, method = 'svr', signature = 'ABIS_S0') ## ----fig.retina = 1----------------------------------------------------------- # plot pearson correlation between predictions and true proportions plot_benchmark(benchmarked = bench, metric = 'pcc') ## ----results='hide'----------------------------------------------------------- # deconvolute input data using selected methods and reference profile matrix methods <- c('ols','nnls','qprog','rls','svr') decon <- deconvolute(bulkRNAseq_ABIS, list(ABIS_S2 = sigMatrix_ABIS_S2), methods) ## ----------------------------------------------------------------------------- # correlation analysis correl <- correlate(deconvoluted = decon) ## ----fig.retina = 1----------------------------------------------------------- # correlation heatmap plot_correlate(correlated = correl, method="heatmap", legend=TRUE) ## ----------------------------------------------------------------------------- # correlation mean summary statistics head(correl$summary) ## ----------------------------------------------------------------------------- # deconvolution method ranking head(correl$rank) ## ----------------------------------------------------------------------------- # print session info sessionInfo()