In AlexsLemonade/scpcaTools: Single cell data tools for ScPCA

CITE-seq Experiment Summary

CITE-seq Statistics

# add rowData if missing
if (is.null(rowData(cite_exp)$detected)) {
  cite_exp <- scuttle::addPerFeatureQCMetrics(cite_exp)
}

cell_adt_counts <- Matrix::colSums(counts(cite_exp))

cite_information <- tibble::tibble(
  "Number of ADTs assayed" =
    format(nrow(cite_exp), big.mark = ",", scientific = FALSE),
  "CITE-seq reads sequenced" =
    format(cite_meta$total_reads, big.mark = ",", scientific = FALSE),
  "Percent CITE-seq reads mapped to ADTs" =
    paste0(round(cite_meta$mapped_reads / cite_meta$total_reads * 100, digits = 2), "%"),
  "Percent of ADTs in cells" =
    paste0(round(sum(cell_adt_counts) / cite_meta$mapped_reads * 100, digits = 2), "%"),
  "Percent of cells with ADTs" =
    paste0(round(sum(cell_adt_counts > 0) / length(cell_adt_counts) * 100, digits = 2), "%"),
  "Median ADT UMIs per cell" =
    format(median(cell_adt_counts), big.mark = ",", scientific = FALSE)
) |>
  t()

knitr::kable(cite_information, align = "r") |>
  kableExtra::kable_styling(
    bootstrap_options = "striped",
    full_width = FALSE,
    position = "left"
  ) |>
  kableExtra::column_spec(2, monospace = TRUE)

Antibody Derived Tag Statistics

antibody_tags <- as.data.frame(rowData(cite_exp)) |>
  tibble::rownames_to_column("Antibody") |>
  arrange(desc(mean)) |>
  select("Antibody",
    "Mean UMI count per cell" = mean,
    "Percent of cells detected" = detected
  )

knitr::kable(antibody_tags, digits = 2) |>
  kableExtra::kable_styling(
    bootstrap_options = c("striped", "condensed"),
    full_width = FALSE,
    position = "left",
  ) |>
  kableExtra::column_spec(2:3, monospace = TRUE)