summarize_per_region: Transform xyz coordinates data in a summary per brain region

In valeriabonapersona/abc4d: Analysis of Brain Cells in 4 Dimensions

Description

Wrapper around dplyr functions to create a summary dataframe with information about count and intensity per brain area. In the output: count_perthousand refers to the number of cells expressing the protein of interest per thousand of total cells in that brain area, while intensity refers to the average intensity of active cells. You can also specify the type of cells estimated.

Usage

summarize_per_region(xyz_coordinates, estimation_atlas, cells_type = "cells")

Arguments

xyz_coordinates	dataframe where each row is a cell. It contains the following variables: 'sample_id' to describe the sample; 'my_grouping' for the brain areas; 'maxInt' for the maximum intensity of the protein per identified cell.
estimation_atlas	estimation atlas already adjusted for the brain areas of interest. Can be output from adapt_estimation_atlas().
cells_type	type of cells from estimation atlas to be used for count correction. Look at the variables of estimation_atlas for types. If not specified, uses all types.

Examples

x <- data.frame(
sample_id = c(rep("a", 100), rep("b", 75), rep("c", 50)),
my_grouping = c(rep(c("CA1","CA2","CA3", "DG", "BLA"), each = 20),
rep(c("CA1", "CA2", "CA3"), each = 20), rep("BLA", 15), rep(c("DG", "BLA"), each = 25)),
maxInt = abs(rnorm(250, 100))
)

y <- data.frame(
my_grouping = c("CA1","CA2","CA3", "DG", "BLA"),
cells = sample(100000, 5),
glia = sample(10000, 5)
)


summarize_per_region(x,y)

valeriabonapersona/abc4d documentation built on Dec. 23, 2021, 2:09 p.m.