I'm really interested in scRNAutils and want to apply this brilliant procession to project.
Recently I researched this package and related paper before repeat this integration part. Today I installed the newest scRNAutils
version(dev) and to run as the following code step by step used one sample GSM4705589_RPE004_matrix.txt firstly.
raw_counts_processing/process_pan_human_carotid_samples_SCTransform.R
When it came to this step,
I changed names of function and parameter according the new version, like this:
> rpe004_seurat_sct = seuratSCTprocess(rpe004_seurat_sct, libraryID = "pan_rpe004", studyID = "pan_et_al", tissueSource = "Carotid", diseaseStatus = "Atherosclerotic_plaque", seuratFilter = TRUE, age = 83, sex = "Male")
the feedback is:
Setting MAD-based adaptive thresholds for cells filtering... Using 3 MADs for joint metric filtering... Error in split.default(M, B) : first argument must be a vector --
Could you please provide some suggestions? Many thanks!
hi,
I'm really interested in scRNAutils and want to apply this brilliant procession to project. Recently I researched this package and related paper before repeat this integration part. Today I installed the newest scRNAutils version(dev) and to run as the following code step by step used one sample GSM4705589_RPE004_matrix.txt firstly. raw_counts_processing/process_pan_human_carotid_samples_SCTransform.R When it came to this step,
I changed names of function and parameter according the new version, like this:
> rpe004_seurat_sct = seuratSCTprocess(rpe004_seurat_sct, libraryID = "pan_rpe004", studyID = "pan_et_al", tissueSource = "Carotid", diseaseStatus = "Atherosclerotic_plaque", seuratFilter = TRUE, age = 83, sex = "Male")
the feedback is:Setting MAD-based adaptive thresholds for cells filtering... Using 3 MADs for joint metric filtering... Error in split.default(M, B) : first argument must be a vector
-- Could you please provide some suggestions? Many thanks!