massonix / hcatonsildata Goto Github PK

Hey guys,
Congratulation on such amazing work,
I am just having some issues converting the sce to Seurat object

allseurat <- as.Seurat(All)

Error in UseMethod(generic = "as.sparse", object = x) : 
  no applicable method for 'as.sparse' applied to an object of class "c('DelayedMatrix', 'DelayedArray', 'DelayedUnaryIsoOp', 'DelayedUnaryOp', 'DelayedOp', 'Array', 'RectangularData')"

Would appreciate if you could help with that :D
Thanks a lot

Hi there,

Congrats on a great work, and thanks for developing this package.

I am attempting to pull TCR-seq data for T cells that also have the GEX/CITE-seq Seurat objects.

QUESTION 1. I saw the output of cellranger vdj deposited at https://zenodo.org/record/6678331#.Y_iuOZPP00R within the CITE-seq folder. Would you mind clarifying what the subfolders (shown below, e.g., BCLLATLAST_XX, ifZOgenn_TpMNTvBa, mLuLpVxi_v0fLyotc, etc.) refer to? They are probably sequencing runs and gem ID.

QUESTION 2. I noticed you used scirpy for the immune receptor repertoire analysis, and I could pull TCR from the vdj_t folders "barcode" that matched the cell barcodes of the meta.data of the T cell Seurat objects. But, would you mind letting me know whether you might already have the processed sc-VDJ data for T cells as an R/Python object - the ones that have the matched Seurat GEX/CITE-seq objects for T cells?

QUESTION 3. It looks like only the CITE-seq-ed cells have TCR data, but only Seurat object with ADT imputed was deposited. The cell barcodes are not the same between Seurat GEX object and TCR vdj, so I could not match the cells between these 2 datasets. Do you have CITE-seq Seurat object for CD8 T cells?

Thank you again very much for your help!

PS. I emailed you @massonix per issue #8

Hi, could you please inform where can I find the Visium data in your paper? Thanks~

Hi there,

Thanks again for all of your help in leveraging the great dataset you generated.

I subsetted the whole tonsil cite-seq Seurat object to obtain 2 cite-seq objects (one object for B cells expressing CD38 and one object for B cells not expressing CD38).

I followed the codes you kindly deposited to perform WNN analysis of RNA+ADT for each of these 2 objects, including harmony to integrate by "gem_ID" within each object within each object.

I now hope to merge these 2 B cell objects and cluster them using RNA+ADT.

Would you minding providing some opinion whether I should simply use merge() or what is the recommended workflow?

Thank you very much!

Hi there,

Sorry for another Q.

I downloaded the Seurat objects from Zenodo because the HCATonsilData did not work (issue #9).

However, I encountered another error when attempting to subset cite-seq Seurat object by protein expression. It only worked for protein names that do not have a parenthesis. Yet, VlnPlot, AverageExpression, rownames works fine for these genes. Asked also in satijalab/seurat#6989

Would you mind advising how to proceed?

Thank you for your help.

Are raw counts available for the scRNA-seq data? From the commands history in the Seurat object, seems like the data in the "RNA" slot under assays is normalized.

library(HCATonsilData)
HCATonsilData(assayType="RNA")
#> snapshotDate(): 2021-10-19
#> Error in .local(x, i, j = j, ...): 'i' must be length 1

^{Created on 2022-10-23 by the reprex package (v2.0.1)}

sessioninfo::session_info()
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Dear Ramon and colleagues,

Great work and thank you for making this data available. I am trying to access the data via level 4 (R) using the following command:
devtools::install_github("massonix/HCATonsilData", build_vignettes = TRUE)

However I get the following error message:
**Quitting from lines 117-119 (HCATonsilData.Rmd)
Error: processing vignette 'HCATonsilData.Rmd' failed with diagnostics:
HDF5. File accessibility. Unable to open file.
--- failed re-building 'HCATonsilData.Rmd'

SUMMARY: processing the following file failed:
'HCATonsilData.Rmd'

Error: Vignette re-building failed.
Execution halted**

Apologies if I am doing something wrong - can you please help?

Many thanks

BW

Amit

Hi there,

Thanks for the tool and the dataset.

I downloaded the Seurat object for CD8 T cells (CD8_T_seurat_obj) from https://zenodo.org/record/6340174#.Y_zdmbTP3ao.

The object shows the ADT assay is available, but when access the protein expression levels for any of the proteins, the expression was 0 across cells.

Would you mind providing the cite-seq Seurat object for CD8 T cells?

And, why is the protein expression in the available Seurat object = 0?

Thank you.

Hi Ramon,
Thanks for the great package and dataset - I'm getting an error trying to install:

devtools::install_github("massonix/HCATonsilData", build_vignettes = TRUE) Downloading GitHub repo massonix/HCATonsilData@HEAD ✔ checking for file ‘/private/var/folders/yh/ls2hbq6j7039g1b2ldmrkvbh0000gp/T/Rtmp5lxC9o/remotes9c5c5c953635/massonix-HCATonsilData-59187d4/DESCRIPTION’ (411ms) ─ preparing ‘HCATonsilData’: ✔ checking DESCRIPTION meta-information ... ─ installing the package to build vignettes ----------------------------------- ─ installing *source* package ‘HCATonsilData’ ... ** using staged installation ** R Error in parse(outFile) : /private/var/folders/yh/ls2hbq6j7039g1b2ldmrkvbh0000gp/T/RtmpG6nFZf/Rbuild9c7a4c45bdde/HCATonsilData/R/HCATonsilData.R:52:33: unexpected input 51: "pca", "harmony", "umap") 52: filePaths <- sapply(suffixes, \ ^ ERROR: unable to collate and parse R files for package ‘HCATonsilData’ ─ removing ‘/private/var/folders/yh/ls2hbq6j7039g1b2ldmrkvbh0000gp/T/RtmpG6nFZf/Rinst9c7a76b460f0/HCATonsilData’ ----------------------------------- ERROR: package installation failed Error: Failed to install 'HCATonsilData' from GitHub: System command 'R' failed, exit status: 1, stdout + stderr (last 10 lines): E> ** R E> Error in parse(outFile) : E> /private/var/folders/yh/ls2hbq6j7039g1b2ldmrkvbh0000gp/T/RtmpG6nFZf/Rbuild9c7a4c45bdde/HCATonsilData/R/HCATonsilData.R:52:33: unexpected input E> 51: "pca", "harmony", "umap") E> 52: filePaths <- sapply(suffixes, \ E> ^ E> ERROR: unable to collate and parse R files for package ‘HCATonsilData’ E> * removing ‘/private/var/folders/yh/ls2hbq6j7039g1b2ldmrkvbh0000gp/T/RtmpG6nFZf/Rinst9c7a76b460f0/HCATonsilData’ E> ----------------------------------- E> ERROR: package installation failed

Here's my sessionInfo()

`sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin19.6.0 (64-bit)
Running under: macOS Big Sur 10.16

Matrix products: default
BLAS: /usr/local/Cellar/r/4.0.3/lib/R/lib/libRblas.dylib
LAPACK: /usr/local/Cellar/r/4.0.3/lib/R/lib/libRlapack.dylib

locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

attached base packages:
[1] stats graphics grDevices utils datasets methods base

loaded via a namespace (and not attached):
[1] ps_1.5.0 prettyunits_1.1.1 withr_2.5.0 rprojroot_2.0.2
[5] crayon_1.5.1 R6_2.5.1 lifecycle_1.0.1 magrittr_2.0.3
[9] rlang_1.0.3 cachem_1.0.6 cli_3.3.0 curl_4.3.2
[13] remotes_2.4.2 fs_1.5.2 callr_3.7.0 ellipsis_0.3.2
[17] devtools_2.4.3 tools_4.0.3 glue_1.6.2 purrr_0.3.4
[21] pkgload_1.3.0 fastmap_1.1.0 compiler_4.0.3 processx_3.5.2
[25] pkgbuild_1.2.0 sessioninfo_1.2.2 memoise_2.0.1 usethis_2.1.6`

Any ideas?
Thanks
Dan

Installing GCBC with processedCounts =TRUE gives the following error:

gcbc <- HCATonsilData(assayType = "RNA", cellType = "GCBC", processedCounts = TRUE)
snapshotDate(): 2022-04-26
see ?HCATonsilData and browseVignettes('HCATonsilData') for documentation
loading from cache
see ?HCATonsilData and browseVignettes('HCATonsilData') for documentation
loading from cache
see ?HCATonsilData and browseVignettes('HCATonsilData') for documentation
loading from cache
see ?HCATonsilData and browseVignettes('HCATonsilData') for documentation
loading from cache
see ?HCATonsilData and browseVignettes('HCATonsilData') for documentation
loading from cache
see ?HCATonsilData and browseVignettes('HCATonsilData') for documentation
loading from cache
see ?HCATonsilData and browseVignettes('HCATonsilData') for documentation
loading from cache
Error in H5Fopen(filepath, flags = "H5F_ACC_RDONLY") : 
  HDF5. File accessibility. Unable to open file.

Which doesn't happen with processedCounts = FALSE. Need to look in depth for future versions

1. Change names of the files to upload: change "" in cell types names (ILC_NK, CD8_T, CD4_T, NBC_MBC) to "". In this way, we can easily subset the cell type name given any file name.
2. Ensure I can easily create a SingleCellExperiment from the independent slots. Check in particular the "processed" slot, which might be corrupted (epithelial).
3. Confirm valid metadata. As described here: "When you are satisfied with the representation of your resources in your metadata.csv (or other aptly named csv file) the Bioconductor team member will add the metadata to the production database. Confirm the metadata csv files in inst/extdata/ are valid by by running either ExperimentHubData::makeExperimentHubMetadata()". This can even become a unit test inside testthat.
4. Send mail to email to [email protected]. Ask them to check that everythng is looking good. Ask for the SAS token, which we'll need to upload the data to experimentHub via AzureStor.
5. Once the data lives in ExperimentHub, create functions (HCATonsilData(datatset, cell_type)) to access the data and retrieve a SingleCellExperiment object. Write vignettes to document how this is done, and include a description of all the data modalities.
6. Generate iSEE instances for every cell type with pre-configured settings: (1) run iSEE(sce), (2) configure the panels to display the most relevant info, (3) click the "download" button to copy and paste the initial code, (4) save said code.
7. Discuss with Will the best strategy to host the iSEE shiny apps in the web.
8. Set up a meeting with @federicomarini to discuss next steps (iSEE, SLOcatoR)