In bioinfocz/scdrake: A pipeline for droplet-based single-cell RNA-seq data secondary analysis implemented in the drake Make-like toolkit for R language

We excluded genes that are not expressed in our system and don't contribute any information to our experiment. Very lowly expressed genes may only contribute noise.

Table of zero-expression genes count:

janitor::tabyl(sce_qc_filter_rowSums == 0) %>%
  dplyr::rename(zero_expression = `sce_qc_filter_rowSums == 0`) %>%
  dplyr::mutate(percent = scales::percent(percent)) %>%
  scdrake::render_bootstrap_table(full_width = FALSE, position = "left")

Removing r sum(drake::readd(sce_qc_gene_filter, path = drake_cache_dir)) genes with UMI per cell less than r cfg$MIN_UMI and expressed in less than r cfg$MIN_RATIO_CELLS * 100 % of all cells.

Info on dataset-sensitive filtered dataset:

cat(drake::readd(sce_qc_filter_genes_info, path = drake_cache_dir)$str)

bioinfocz/scdrake documentation built on Sept. 19, 2024, 4:43 p.m.