Description:
Hi, thanks for developing IsoQuant — it’s very helpful for long-read single-cell analysis.
I have a question about handling multiple samples in single-cell mode.
When running multiple independent samples together, cell barcodes may overlap across samples (e.g., the same 10x barcode appearing in different experiments). In this case, it seems IsoQuant:
treats identical barcodes from different samples as the same cell
performs UMI deduplication across samples
merges counts, losing sample identity
Questions:
Is this the expected behavior (i.e., assuming a single pooled experiment)?
Is there a recommended way to preserve sample identity in multi-sample runs?
Currently, it seems necessary to either run samples separately or manually add prefixes to barcodes.
Would it be possible to support something like a sample prefix or per-input-file grouping to avoid barcode collisions?
Thanks!
Description:
Hi, thanks for developing IsoQuant — it’s very helpful for long-read single-cell analysis.
I have a question about handling multiple samples in single-cell mode.
When running multiple independent samples together, cell barcodes may overlap across samples (e.g., the same 10x barcode appearing in different experiments). In this case, it seems IsoQuant:
treats identical barcodes from different samples as the same cell
performs UMI deduplication across samples
merges counts, losing sample identity
Questions:
Is this the expected behavior (i.e., assuming a single pooled experiment)?
Is there a recommended way to preserve sample identity in multi-sample runs?
Currently, it seems necessary to either run samples separately or manually add prefixes to barcodes.
Would it be possible to support something like a sample prefix or per-input-file grouping to avoid barcode collisions?
Thanks!