In oldhamlab/Copeland.2021.hypoxia.flux: What the Package Does (One Line, Title Case)

# load libraries
suppressPackageStartupMessages({
  devtools::load_all()
  library(tidyverse)
  library(wmo)
  library(targets)
})

# set global chunk options
knitr::opts_chunk$set(
    echo = FALSE,
    fig.align = "center",
    message = FALSE,
    warning = FALSE,
    out.width = "49%"
)


options(knitr.table.format = function() {
  if (knitr::is_latex_output()) 
    "latex" else "html"
})

theme_set(theme_wmo(base_family = "Calibri"))

withr::with_dir(here::here(), {
  std <- tar_read(dna_per_cell_std)
  sample <- tar_read(dna_per_cell_clean)
  cells_per_dna <- tar_read(cells_per_dna)
})

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Overview

Cell counts were estimated from total cellular DNA measured by PicoGreen fluorescence (Quant-iT PicoGreen dsDNA Assay Kit, P11496, Thermo). Here, we determine the relationship between total DNA and cell count by quantifying DNA extracted from cells seeded at different densities in basal growth medium. For the lung fibroblasts, cells were extracted with 100 μL or 200 μL of TE buffer with 0.2% Triton X-100. Earlier experiments used the smaller volume of extraction buffer and this is adjusted for during the extracellular flux calculations.

Analysis

Standard Curves

std %>% 
  unnest(c(summary)) %>% 
  ggplot() +
  aes(y = reorder(date, desc(date)), x = r.squared) +
  geom_point() +
  labs(
    y = "Date", 
    x = expression(paste("R"^2))
  )

Samples

sample %>% 
  ggplot() +
  aes(x = cells, y = conc) +
  facet_wrap(~ cell_type * volume, labeller = as_labeller(toupper)) +
  geom_point(alpha = 0.3) +
  stat_summary(
    geom = "pointrange", 
    fun.data = "mean_se"
  ) +
  geom_smooth(
    method = "lm", 
    formula = y ~ 0 + x, 
    se = FALSE
  ) +
  labs(
    x = "Cell count", 
    y = "DNA (ng)"
  )

These plots suggest that, for the 100 μL extraction buffer, the maximum cell count is ~ 250,000. We will exclude the 300,000 value prior to calculate the slopes of the curves. For the PASMC samples, the 400,000 cell sample is quite high compared to the other samples. Will also remove these values prior to calculation of the slopes.

\newpage

usethis::use_data(cells_per_dna, overwrite = TRUE)

cells_per_dna  %>% 
  my_kable(
    digits = 0, 
    col.names = c("Cell Type", "Volume", "Cell / DNA"), 
    align = "c", 
    caption = "Cells per DNA (ng)"
  ) %>% 
  kableExtra::kable_styling(position = "center") 

oldhamlab/Copeland.2021.hypoxia.flux documentation built on Feb. 5, 2022, 8:31 p.m.