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Thank you very much for open sourcing such a great single cell tool. I have been using it from 3.0 until now 4.0 and it has helped me a lot.
But in the recent 4.0, I have encountered some problems. I can work fine using the data you provided. But when using my own data, it prompts an error.
I input these data like this:
cpdb_file_path = '/Users/zhuyewen/Downloads/CellphoneDB-master/db/v4.1.0/cellphonedb.zip'
meta_file_path = '/Users/zhuyewen/R/技术摸索/23.cellphonedb/metadata.tsv'
counts_file_path = '/Users/zhuyewen/R/技术摸索/23.cellphonedb/pbmc3k.h5ad'
out_path = '/Users/zhuyewen/Downloads/CellphoneDB-master/result/method2'
...
from cellphonedb.src.core.methods import cpdb_statistical_analysis_method
deconvoluted, means, pvalues, significant_means = cpdb_statistical_analysis_method.call(
cpdb_file_path = cpdb_file_path, # mandatory: CellPhoneDB database zip file.
meta_file_path = meta_file_path, # mandatory: tsv file defining barcodes to cell label.
counts_file_path = counts_file_path, # mandatory: normalized count matrix.
counts_data = 'hgnc_symbol', # defines the gene annotation in counts matrix.
# microenvs_file_path = microenvs_file_path, # optional (default: None): defines cells per microenvironment.
iterations = 1000, # denotes the number of shufflings performed in the analysis.
threshold = 0.1, # defines the min % of cells expressing a gene for this to be employed in the analysis.
threads = 4, # number of threads to use in the analysis.
debug_seed = 42, # debug randome seed. To disable >=0.
result_precision = 3, # Sets the rounding for the mean values in significan_means.
pvalue = 0.05, # P-value threshold to employ for significance.
subsampling = False, # To enable subsampling the data (geometri sketching).
subsampling_log = False, # (mandatory) enable subsampling log1p for non log-transformed data inputs.
subsampling_num_pc = 100, # Number of componets to subsample via geometric skectching (dafault: 100).
subsampling_num_cells = 1000, # Number of cells to subsample (integer) (default: 1/3 of the dataset).
separator = '|', # Sets the string to employ to separate cells in the results dataframes "cellA|CellB".
debug = False, # Saves all intermediate tables employed during the analysis in pkl format.
output_path = out_path, # Path to save results.
output_suffix = None # Replaces the timestamp in the output files by a user defined string in the (default: None).
)
And I got this error
ParseCountsException: Invalid Counts data
Here's how I generated the expression matrix file in Rstudio
I am not sure if there is something wrong with the code I used to generate the h5ad file, if so could you please provide the code on how to generate that file using R language?
I browsed through all the issues and found no similar questions or answers. I hope you have time to tell me how to generate h5ad from Seurat object by R, and hopefully provide a solution for people who encounter the same problem later. Thanks a lot.
My platform: MacOs13.3, Apple M1 Ultra, R version 4.3.0, python = 3.8
Best regard
Yewen Zhu
The text was updated successfully, but these errors were encountered:
Hello, cellphonedb team!
Thank you very much for open sourcing such a great single cell tool. I have been using it from 3.0 until now 4.0 and it has helped me a lot.
But in the recent 4.0, I have encountered some problems. I can work fine using the data you provided. But when using my own data, it prompts an error.
I input these data like this:
And I got this error
ParseCountsException: Invalid Counts data
Here's how I generated the expression matrix file in Rstudio
I am not sure if there is something wrong with the code I used to generate the h5ad file, if so could you please provide the code on how to generate that file using R language?
I browsed through all the issues and found no similar questions or answers. I hope you have time to tell me how to generate h5ad from Seurat object by R, and hopefully provide a solution for people who encounter the same problem later. Thanks a lot.
My platform: MacOs13.3, Apple M1 Ultra, R version 4.3.0, python = 3.8
Best regard
Yewen Zhu
The text was updated successfully, but these errors were encountered: