Open klgoss opened 2 years ago
Hi, Please see the description in "https://github.com/zhanglhbioinfor/DIRECT-NET/issues/2". Could you please reinstall the package and then run the function?
For testing all markers, please use pbmc <- Run_DIRECT_NET(pbmc, peakcalling = FALSE, k_neigh = 50, atacbinary = TRUE, max_overlap=0.5, size_factor_normalize = FALSE, genome.info = genome.info, focus_markers = markers_groups)
That worked. Thank you very much!
Hi and thank you for developing this library. I am getting the same error when I run the PBMC tutorial exactly as it is (except marker finding part since presto is not available for R version 4 on CRAN but looking at the code I don't think that should be an issue). Previously suggested solutions didn't work so is there any update on what is the reason for this error?
I traced down this error and it seems like when Run_DIRECT_NET calls Aggregate_data function, it doesn't pass size_factor_normalization parameter, hence the default value TRUE is passed to this function. I changed the call function to agg.data <- Aggregate_data(object, size_factor_normalize = size_factor_normalize) at line 477 and it works in my environment.
Hi! Thanks for your kindly suggestion! I have updated the function.
Hello, I am very excited to use DIRECT-NET on our upcoming datasets. In the meantime, I've tried testing DIRECT-NET on publicly available 10X Multiome data (following the WNN workflow from Seurat https://satijalab.org/seurat/articles/weighted_nearest_neighbor_analysis.html#wnn-analysis-of-10x-multiome-rna-atac-1).
Once I get to the DIRECT-NET function, I am getting the following error:
pbmc <- Run_DIRECT_NET(pbmc, peakcalling = FALSE, k_neigh = 50, atacbinary = TRUE, max_overlap=0.5, size_factor_normalize = FALSE, genome.info = genome.info, focus_markers = c("GLB1","TAF1B"))
Generating aggregated data Aggregating cluster CD4 Naive Sample cells randomly. Aggregating cluster CD4 TCM Sample cells randomly. Aggregating cluster CD8 Naive Sample cells randomly. Aggregating cluster CD16 Mono Sample cells randomly. Aggregating cluster NK Sample cells randomly. Aggregating cluster Treg Sample cells randomly. Aggregating cluster CD14 Mono Sample cells randomly. Aggregating cluster cDC Sample cells randomly. Aggregating cluster CD8 TEM_1 Sample cells randomly. Aggregating cluster Intermediate B Sample cells randomly. Aggregating cluster Memory B Sample cells randomly. Aggregating cluster Plasma Aggregating cluster CD4 TEM Sample cells randomly. Aggregating cluster MAIT Sample cells randomly. Aggregating cluster Naive B Sample cells randomly. Aggregating cluster gdT Sample cells randomly. Aggregating cluster CD8 TEM_2 Sample cells randomly. Aggregating cluster pDC Sample cells randomly. Aggregating cluster HSPC Error in h(simpleError(msg, call)) : error in evaluating the argument 'x' in selecting a method for function 't': the condition has length > 1
Could someone advise me on how to proceed? Additionally, how would I go about testing all markers, not just focus markers? Thank you.