In pmlnado/flowmalizr: Normalizing Cell Population Percentages

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Flowmalizr takes an xls input sheet containing columns listed as groups, total_cell_count_per_mL, live_cells, and phenotypes of interest. these contain a group-replicate, cell number per mL, live cell count, and cells identified, respectively. This is used to detemine cells_from_total and percentage of total by (total_cell_count_per_mLcells-of-phenotype/live_cells)100. The output from this function is a dataframe that can be manipulated for visualization of cell phenotypes from each group.

The rest of this package uses functions as commands to further interpret and visualize the data.

sep_groups()

unique_pops()

visualize_groups()

group_v_group(groupA, groupB)

Load flowmalizr()

library(flowmalizr)

Read in the raw file and name it as path_to_data

path_to_data <- system.file("extdata", "example_data.xlsx", package = "flowmalizr")

flowmalizr(path = path_to_data)

Separate group and replicate into their own columns

sep_groups()

Pull unique gated populations

unique_pops()

Plot percentage of populations per group

visualize_groups()

1v1 comparison: Enter no more than two groups to compare their phenotypic responses.

group_v_group(1,3)

pmlnado/flowmalizr documentation built on May 20, 2022, 3:19 a.m.