diff --git a/vignettes/decoupleR.Rmd b/vignettes/decoupleR.Rmd index 914009f..cbb02c4 100644 --- a/vignettes/decoupleR.Rmd +++ b/vignettes/decoupleR.Rmd @@ -179,6 +179,7 @@ res_gsea <- decoupleR::run_fgsea(mat = mat, .target = 'target', nproc = 1, minsize = 0) + res_gsea ``` @@ -202,6 +203,7 @@ res_ulm <- decoupleR::run_ulm(mat = mat, .target = 'target', .mor = 'mor', minsize = 0) + res_ulm ``` @@ -285,6 +287,7 @@ res_decouple <- decoupleR::decouple(mat, .source ='source', .target ='target', minsize = 0) + res_decouple ``` diff --git a/vignettes/pw_bk.Rmd b/vignettes/pw_bk.Rmd index 441ae94..4971d47 100644 --- a/vignettes/pw_bk.Rmd +++ b/vignettes/pw_bk.Rmd @@ -86,6 +86,7 @@ head(counts) The design meta-data: ```{r "design"} design <- data$design + design ``` @@ -197,6 +198,7 @@ contrast_acts <- decoupleR::run_mlm(mat =deg, .target = 'target', .mor = 'weight', minsize = 5) + contrast_acts ``` diff --git a/vignettes/tf_bk.Rmd b/vignettes/tf_bk.Rmd index 67538c6..ff5cbdf 100644 --- a/vignettes/tf_bk.Rmd +++ b/vignettes/tf_bk.Rmd @@ -79,12 +79,14 @@ counts <- data$counts %>% ~ dplyr::if_else(is.na(.x), 0, .x)) %>% tibble::column_to_rownames(var = "gene") %>% as.matrix() + head(counts) ``` The design meta-data: ```{r "design"} design <- data$design + design ``` @@ -97,6 +99,7 @@ deg <- data$limma_ttop %>% dplyr::filter(!is.na(t)) %>% tibble::column_to_rownames(var = "ID") %>% as.matrix() + head(deg) ``` @@ -118,6 +121,7 @@ recommend to keep complexes together. ```{r "collectri"} net <- decoupleR::get_collectri(organism = 'human', split_complexes = FALSE) + net ``` @@ -140,6 +144,7 @@ sample_acts <- decoupleR::run_ulm(mat = counts, .target = 'target', .mor = 'mor', minsize = 5) + sample_acts ``` @@ -199,6 +204,7 @@ contrast_acts <- decoupleR::run_ulm(mat = deg[, 't', drop = FALSE], .target = 'target', .mor='mor', minsize = 5) + contrast_acts ``` @@ -247,6 +253,7 @@ p <- ggplot2::ggplot(data = f_contrast_acts, panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + ggplot2::xlab("TFs") + p ``` @@ -295,6 +302,7 @@ p <- ggplot2::ggplot(data = df, ggplot2::geom_vline(xintercept = 0, linetype = 'dotted') + ggplot2::geom_hline(yintercept = 0, linetype = 'dotted') + ggplot2::ggtitle(tf) + p ``` diff --git a/vignettes/tf_sc.Rmd b/vignettes/tf_sc.Rmd index 93afe09..c75c4ec 100644 --- a/vignettes/tf_sc.Rmd +++ b/vignettes/tf_sc.Rmd @@ -69,6 +69,7 @@ p <- Seurat::DimPlot(data, label = TRUE, pt.size = 0.5) + Seurat::NoLegend() + p ``` @@ -90,6 +91,7 @@ recommend to keep complexes together. ```{r "collectri"} net <- decoupleR::get_collectri(organism = 'human', split_complexes = FALSE) + net ``` @@ -115,6 +117,7 @@ acts <- decoupleR::run_ulm(mat = mat, .target = 'target', .mor='mor', minsize = 5) + acts ``` @@ -168,7 +171,9 @@ p3 <- Seurat::FeaturePlot(data, ggplot2::ggtitle('PAX5 expression') Seurat::DefaultAssay(data) <- "tfsulm" + p <- p1 | p2 | p3 +p ``` # Exploration @@ -176,6 +181,7 @@ We can also see what is the mean activity per group of the top 20 more variable TFs: ```{r "mean_acts", message = FALSE, warning = FALSE} n_tfs <- 25 + # Extract activities from object as a long dataframe df <- t(as.matrix(data@assays$tfsulm@data)) %>% as.data.frame() %>%