library(tidyheatmaps) tidyheatmap(df = data_exprs, rows = external_gene_name, columns = sample, values = expression, scale = "row", annotation_col = c(sample_type, condition, group), annotation_row = c(is_immune_gene, direction), gaps_row = direction, gaps_col = group )

This is how you can visualize gene expression data in #tidyheatmaps 🤩

https://jbengler.github.io/tidyheatmaps/

#rstats #dataviz #phd

library(tidyheatmaps) tidyheatmap(df = data_exprs, rows = external_gene_name, columns = sample, values = expression, scale = "row", annotation_col = c(sample_type, condition, group), annotation_row = c(is_immune_gene, direction), gaps_row = direction, gaps_col = group )

This is how you can visualize gene expression data in #tidyheatmaps 🤩

https://jbengler.github.io/tidyheatmaps/

#rstats #dataviz #phd

library(tidyheatmaps) tidyheatmap(df = data_exprs, rows = external_gene_name, columns = sample, values = expression, scale = "row", annotation_col = c(sample_type, condition, group), annotation_row = c(is_immune_gene, direction), gaps_row = direction, gaps_col = group )

This is how you can visualize gene expression data in #tidyheatmaps 🤩

jbengler.github.io/tidyheatmaps/

#rstats #dataviz #phd

Heatmaps from Tidy Data The goal of tidyheatmaps is to simplify the generation of publication-ready heatmaps from tidy data. By offering an interface to the powerful pheatmap package, it allows for the effortless creation of...

#tidyheatmaps Another way to show heatmaps #rstats jbengler.github.io/tidyheatmaps/

library(tidyheatmaps) tidyheatmap(df = data_exprs, rows = external_gene_name, columns = sample, values = expression, scale = "row", annotation_col = c(sample_type, condition, group), annotation_row = c(is_immune_gene, direction), gaps_row = direction, gaps_col = group )

This is how you can visualize gene expression data in #tidyheatmaps 🤩

jbengler.github.io/tidyheatmaps/

#rstats #dataviz #phd