soumelis-lab / icellnet Goto Github PK

Is the Lupus_Seurat_SingleCell_Landscape.Rds file available to download? The data is not available in the links present in the paper.

Hi,

Could you please advice me how to download PC.data.all and PC.target.all objects from the github? I cloned the repository, and then attempted git lfs pull to download the files, but I get the following error

batch response: This repository is over its data quota. Account responsible for LFS bandwidth should purchase more data packs to restore access.                          
error: failed to fetch some objects from 'https://github.com/soumelis-lab/ICELLNET.git/info/lfs'

Thanks in advanced!

Eyleen

I am just following the example data and get an error below

Convert the gene symbol to affy ID

PC.affy.probes = as.data.frame(PC.data[,c(1,2)])
PC.affy.probes$ID = rownames(PC.affy.probes) # for format purpose
transform = db.hgu133plus2(db2,PC.affy.probes) # creation of a new db2 database with AffyID instead of gene symbol
Error in .testForValidKeys(x, keys, keytype, fks) :
None of the keys entered are valid keys for 'PROBEID'. Please use the keys method to see a listing of valid arguments.

Hi,

I'm following the tutorial to the letter and having the following error:

> transform = db.hgu133plus2(db2,PC.affy.probes) # creation of a new db2 database with AffyID instead of gene symbol
'select()' returned 1:many mapping between keys and columns
Error in get(paste("scores.", chip, sep = "")) : 
  object 'scores.hgu133plus2' not found

It seems that jmap::jetset() is considering somehow the eg option and searching for missing scores.

Any idea about if I miss-considering something, please? Thanks

TLDR

> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS  10.16

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/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] icellnet_1.0.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.8           IRanges_2.24.1       DBI_1.1.2            stats4_4.0.2         RSQLite_2.2.9        rlang_1.0.1          cachem_1.0.6        
 [8] cli_3.1.1            curl_4.3.2           blob_1.2.2           S4Vectors_0.28.1     vctrs_0.3.8          org.Hs.eg.db_3.11.4  tools_4.0.2         
[15] bit64_4.0.5          Biobase_2.50.0       bit_4.0.4            jetset_3.4.0         parallel_4.0.2       fastmap_1.1.0        compiler_4.0.2      
[22] pkgconfig_2.0.3      BiocGenerics_0.36.0  AnnotationDbi_1.50.3 memoise_2.0.1        hgu133plus2.db_3.2.3

Thank you for the examples and explanations you provide. Could you also upload or link the txt files you use in the two case studies? I would like to replicate your steps before trying with my own data.

I am trying to use Visium data. However, it seems ICELLNET do not support Visium RDS data as it shows an error when I am trying to implement this code:
average.clean= sc.data.cleaning(object = seurat, db = db, filter.perc = filter.perc, save_file = T, path="path/", force.file = F)

This is the error:
"Error: Cannot find 'RNA' in this Seurat object"

In the RDS file saved from processed seurat object from visium, there are two data on assays: Spatial and SCT and there is no RNA.
Do you have any solution?

Hi, I am encountering an error. Could you please help me fix it? Thank you so much!
Here's the code.

`library(BiocGenerics)
library("org.Hs.eg.db")
library("hgu133plus2.db")
library(jetset)
library(ggplot2)
library(dplyr)
library(icellnet)
library(gridExtra)

db=as.data.frame(read.csv(curl::curl(url="https://raw.githubusercontent.com/soumelis-lab/ICELLNET/master/data/ICELLNETdb.tsv"), sep="\t",header = T, check.names=FALSE, stringsAsFactors = FALSE, na.strings = ""))

my.selection.LR=c("Cytokine")
db2 <- db[grepl(paste(my.selection.LR, collapse="|"),db$Classifications),] if you want to use all the database, do instead : db2=db
db2$Subfamily=db2$Cytokines to define subfamily of interest as cytokines.
db.name.couple=name.lr.couple(db2, type="Subfamily")
head(db.name.couple)`

download PC.data.all and PC.target.all objects from the github and open them on your Rstudio session - adapt path if needed
PC.data.all=as.data.frame(read.csv("../PC.data.all.csv", sep=",", header = T, check.names=FALSE, stringsAsFactors = FALSE, na.strings = ""))

rownames(PC.data.all)=PC.data.all$ID

PC.target.all=as.data.frame(read.csv("../PC.target.all.csv", sep=",",header = T, check.names=FALSE, stringsAsFactors = FALSE, na.strings = ""))

my.selection=c("Epith", "Fblast_B", "Endoth","Mono", "Macroph", "pDC", "DC2", "DC1", "NK", "Neutrop","CD4 T cell","CD8 T cell", "Treg","B cell")

PC.target = PC.target.all[which(PC.target.all$Class%in%my.selection|PC.target.all$Class%in%my.selection),c("ID","Class","Cell_type")]
Error in [.data.frame`(PC.target.all, which(PC.target.all$Class %in% : undefined columns selected

stop("undefined columns selected")

[.data.frame(PC.target.all, which(PC.target.all$Class %in% my.selection | PC.target.all$Class %in% my.selection), c("ID", "Class", "Cell_type"))
1.

PC.target.all[which(PC.target.all$Class %in% my.selection | PC.target.all$Class %in% my.selection), c("ID", "Class", "Cell_type")]`

PC.data = PC.data.all[,PC.target$ID]

Error in [.data.frame(PC.data.all, , PC.target$ID) : object 'PC.target' not found

Hi there,
Thank you for developing such a great tool. I am studying intercellular communication between two cell types for which I have RNA-Seq transcriptional profiles. I am defining one cell type as "Central Cell" and the other as "Partner Cell". How can I implement ICELLNET tool to use my own RNA-Seq datasets in this context? Could you please provide an adapted script for this purpose?
Thank you.
Hussein

Hi there,
I've tried running a Seurat object through the pipeline however, when I get to LR.family.score I get the above error
I've noticed that my score1 seems to be 0 for both cell types?
Everything else has run so far so thank you for providing such a nice pipeline

thanks
Rachel

where is the full vignette?

Hello, I was running through the first vignette with the cytokine interaction in CAF-S1 and S4 and noticed my numbers in the figures aren't the same as shown in the vignette figures. It seems mostly to be a scaling issue but the p-value heat map was significantly different. Any feedback or assistance would be greatly appreciated. Thanks in advance.

Hi there,
Thanks so much!
Would you be able to advise me as to how I can adapt the celltalkDB to fit the ICELLNET database format?
It seems I would have to adapt the R code of the db.hgu133plus2() function to have the adapted annotation conversion when using ICELLNET?
But as I'm fairly new to R still i'd definitely appreciate any advice on how to go about doing this

thanks so much for your time
Rachel

Originally posted by @rachel662 in #2 (comment)