CRAWDAD
enables the characterization of cell-type
relationships across different scales.
CRAWDAD
is a statistical framework that uses labeled
spatial omics data to identify the colocalization or separation of cell
types at different scales. CRAWDAD identifies regions where multiple
cells colocalize, the scale of such colocalization, and also subsets the
cell types based on their proximity to others. Therefore, CRAWDAD is a
powerful tool for tissue characterization and comparison.
To install CRAWDAD
, we recommend using
remotes
:
require(remotes)
remotes::install_github('JEFworks-Lab/CRAWDAD')
library(crawdad)
library(tidyverse)
## load the spleen data of the pkhl sample
data('pkhl')
## convert dataframe to spatial points (SP)
cells <- crawdad::toSP(pos = pkhl[,c("x", "y")], celltypes = pkhl$celltypes)
## define the scales to analyze the data
scales <- c(100, 200, 300, 400, 500, 600, 700, 800, 900, 1000)
## shuffle cells to create null background
shuffle.list <- crawdad:::makeShuffledCells(cells,
scales = scales,
perms = 3,
ncores = 7,
seed = 1,
verbose = TRUE)
## calculate the zscore for the cell-type pairs at different scales
results <- crawdad::findTrends(cells,
dist = 100,
shuffle.list = shuffle.list,
ncores = 7,
verbose = TRUE,
returnMeans = FALSE)
dat <- crawdad::meltResultsList(results, withPerms = TRUE)
## calculate the zscore for the multiple-test correction
ntests <- length(unique(dat$reference)) * length(unique(dat$reference))
psig <- 0.05/ntests
zsig <- round(qnorm(psig/2, lower.tail = F), 2)
## summary visualization
vizColocDotplot(dat, zsig.thresh = zsig, zscore.limit = 2*zsig) +
theme(axis.text.x = element_text(angle = 35, h = 0))
## visualize trend for one cell-type pair
dat %>%
filter(reference == 'Podoplanin') %>%
filter(neighbor == 'CD4 Memory T cells') %>%
vizTrends(lines = TRUE, withPerms = TRUE, sig.thresh = zsig)
More details can be found in the tutorials.
To install CRAWDAD
, we recommend using
remotes
:
require(remotes)
remotes::install_github('JEFworks-Lab/CRAWDAD')
We welcome any bug reports, enhancement requests, general questions,
and other contributions. To submit a bug report or enhancement request,
please use the CRAWDAD
GitHub issues tracker. For more
substantial contributions, please fork this repo, push your changes to
your fork, and submit a pull request with a good commit message.