knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%", dpi = 200 ) set.seed(0)
The goal of PackageBluishgreen
is to package the internals for clustering cells for Olesja Popow (pronounced "po-pow").
The cells were identified using a separate algorithm which output DAPI and FITC values for each cell into a CSV.
This package maintains this data in a data structure called tissue_slide
and manages any classification methods applied to the cells.
You can install the released version of 'PackageBluishgreen' from GitHub with:
#> If using 'renv' renv::install("Kevin-Haigis-Lab/PackageBluishgreen") #> else devtools::install_github("Kevin-Haigis-Lab/PackageBluishgreen")
The full documentation can be found here. For examples, check out the vignettes.
If there is a specific classification method you would like, please open an issue on GitHub.
library(PackageBluishgreen)
The tissue slide class is designed to hold three things:
A new tissue slide can be created by just passing in the slide data.
pancreas_data <- read.csv(system.file( "extdata", "unmicst-OP1181_pancreas_TUNEL_01.csv", package = "PackageBluishgreen" )) pancreas_data <- pancreas_data[, c(1, 3:5)] colnames(pancreas_data) <- c("cell_id", "fitc", "x", "y") pancreas_slide <- tissue_slide(pancreas_data, metadata = list(tissue = "pancreas", mouse = "OP1181"))
The metadata can be easily retrieved.
get_slide_metadata(pancreas_slide)
It is also very easy to plot the data.
plot_tissue(pancreas_slide, color = log10(fitc))
A more thorough guide can be found in the "Manual classification" vignette.
The cluster_manually()
function should be used to apply a manual classification cutoff to the data.
pancreas_slide <- cluster_manually(pancreas_slide, fitc, 4.3, transform = log10)
The results can be easily plotted.
plot_slide_clusters(pancreas_slide, method = "manual")
A summary of the results can be obtained using the summarize_cluster_results()
function.
summarize_cluster_results(pancreas_slide)
Mistakes or questions? Open an issue on Github.
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