Last updated: 2021-09-09
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Knit directory: mistyMBC/
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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/cellcomm_misty.Rmd) and HTML (docs/cellcomm_misty.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | aa6ca6b | Jovan Tanevski | 2021-09-09 | Build site. |
| html | 2438eb2 | Jovan Tanevski | 2021-09-09 | Build site. |
| html | e0c1952 | Jovan Tanevski | 2021-07-22 | Build site. |
| Rmd | 3e63dcc | Jovan Tanevski | 2021-07-22 | use normalized hvg, add ligand-pathway pipeline |
| html | 4dd6a02 | Jovan Tanevski | 2021-07-14 | Build site. |
| Rmd | 125da67 | Jovan Tanevski | 2021-07-14 | add slideseq cellcomm pipeline and outputs |
| html | 125da67 | Jovan Tanevski | 2021-07-14 | add slideseq cellcomm pipeline and outputs |
library(reticulate)
library(mistyR)
library(future)
library(dplyr)
library(purrr)
library(OmnipathR)
library(stringr)
library(progeny)
use_python("/usr/local/bin/python3")
plan(multisession)Requires python3 and anndata installed (pip install anndata).
import anndata
import numpy
def read_and_extract(datapath):
adata = anndata.read(datapath)
ots = adata.obsm["OT"]
counts = adata.X
geom = adata.obs[["x_orig", "y_orig"]]
markers = adata.var_names.values
return ots, counts, geom, markersGet ligand and receptor symbols from Omnipath
extract_symbols <- function(op.source) {
proteins <- op.source %>%
filter(entity_type == "protein") %>%
pull(genesymbol)
complexes <- op.source %>%
filter(entity_type == "complex") %>%
pull(genesymbol) %>%
str_remove("COMPLEX:") %>%
str_split("_") %>%
unlist()
return(union(proteins, complexes) %>% make.names())
}
op.ligands <- import_omnipath_intercell(
categories = "ligand",
secreted = TRUE,
consensus_percentile = 50
)
ligands <- extract_symbols(op.ligands)
op.receptors <- import_omnipath_intercell(
categories = "receptor",
secreted = FALSE,
consensus_percentile = 50
)
receptors <- extract_symbols(op.receptors)Define and run ligand receptor and ligand pathway oriented mistyR pipelines for MBC cells in SlideSeq data. Relate expression of genes annotated as ligands in the neighborhood of each MBC cell to its intracellular receptor expression or estimated pathway activities.
# 364 is a tricky sample
(list.files("data", ".h5ad", recursive = TRUE, full.names = TRUE) %>%
keep(~ str_detect(.x, "slide_seq")))[-4] %>%
walk(function(datapath) {
data <- py$read_and_extract(datapath)
mbs <- which(data[[1]][, which(str_detect(colnames(data[[1]]), "MBC"))] >= 0.9)
expr <- as.data.frame((data[[2]])) %>%
slice(mbs) %>%
`colnames<-`(make.names(data[[4]]))
pos <- data[[3]] %>% slice(mbs)
unique(str_extract(rownames(pos), "-\\d$")) %>% walk(function(replicate) {
output.folder <- paste0(
str_replace(
str_remove(datapath, ".h5ad"),
"data", "output"
), replicate
)
if (!dir.exists(output.folder)) dir.create(output.folder)
ind <- str_which(rownames(pos), paste0(replicate, "$"))
if (length(list.files(output.folder)) < 2) {
ligand.views <- create_initial_view(expr[ind, ] %>%
select(-names(which(apply(., 2, var) == 0))) %>%
select(any_of(ligands))) %>%
add_paraview(pos[ind, ], 100)
}
if (!(dir.exists(paste0(output.folder, "/ligrcp")) |
dir.exists(paste0(output.folder, "/ligrcp_failed")))) {
misty.views.ligrcp <- create_initial_view(expr[ind, ] %>%
select(-names(which(apply(., 2, var) == 0))) %>%
select(any_of(receptors))) %>%
add_views(list(ligand.views[["paraview.100"]]))
tryCatch(
run_misty(misty.views.ligrcp, results.folder = paste0(output.folder, "/ligrcp")),
error = function(e) {
file.rename(
paste0(output.folder, "/ligrcp"),
paste0(output.folder, "/ligrcp_failed")
)
}
)
}
if (!(dir.exists(paste0(output.folder, "/ligpath")) |
dir.exists(paste0(output.folder, "/ligpath_failed")))) {
path.activity <- progeny(expr = t(expr[ind, ]), top = 500, scale = TRUE) %>%
as_tibble(.name_repair = make.names)
misty.views.ligpath <- create_initial_view(as_tibble(path.activity)) %>%
add_views(list(ligand.views[["paraview.100"]]))
tryCatch(
run_misty(misty.views.ligpath, results.folder = paste0(output.folder, "/ligpath")),
error = function(e) {
file.rename(
paste0(output.folder, "/ligpath"),
paste0(output.folder, "/ligpath_failed")
)
}
)
}
})
})
sessionInfo()R version 4.1.1 (2021-08-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] progeny_1.14.0 stringr_1.4.0 OmnipathR_3.0.4 purrr_0.3.4
[5] dplyr_1.0.7 future_1.22.1 mistyR_1.1.9 reticulate_1.20
[9] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] httr_1.4.2 sass_0.4.0 tidyr_1.1.3 bit64_4.0.5
[5] vroom_1.5.4 jsonlite_1.7.2 bslib_0.3.0 assertthat_0.2.1
[9] cellranger_1.1.0 yaml_2.2.1 progress_1.2.2 ggrepel_0.9.1
[13] globals_0.14.0 pillar_1.6.2 backports_1.2.1 lattice_0.20-44
[17] glue_1.4.2 digest_0.6.27 promises_1.2.0.1 checkmate_2.0.0
[21] colorspace_2.0-2 htmltools_0.5.2 httpuv_1.6.2 Matrix_1.3-4
[25] pkgconfig_2.0.3 logger_0.2.1 listenv_0.8.0 scales_1.1.1
[29] whisker_0.4 later_1.3.0 tzdb_0.1.2 git2r_0.28.0
[33] tibble_3.1.4 generics_0.1.0 ggplot2_3.3.5 ellipsis_0.3.2
[37] magrittr_2.0.1 crayon_1.4.1 readxl_1.3.1 evaluate_0.14
[41] fs_1.5.0 fansi_0.5.0 parallelly_1.27.0 xml2_1.3.2
[45] tools_4.1.1 prettyunits_1.1.1 hms_1.1.0 lifecycle_1.0.0
[49] munsell_0.5.0 compiler_4.1.1 jquerylib_0.1.4 rlang_0.4.11
[53] grid_4.1.1 rappdirs_0.3.3 igraph_1.2.6 rmarkdown_2.10
[57] gtable_0.3.0 codetools_0.2-18 DBI_1.1.1 curl_4.3.2
[61] R6_2.5.1 gridExtra_2.3 knitr_1.33 bit_4.0.4
[65] fastmap_1.1.0 utf8_1.2.2 rprojroot_2.0.2 readr_2.0.1
[69] stringi_1.7.4 parallel_4.1.1 Rcpp_1.0.7 vctrs_0.3.8
[73] png_0.1-7 tidyselect_1.1.1 xfun_0.25