I ran sicelore 2.1 workflow for my sample. Based on loading concentrations as well as a short-read experiment we performed on the same sample, we expect little over 17 000 unique cell barcodes in our sample. However, when running sicelore, I end up with over 90 000 barcodes. Of course, the large majority of these have only a very low number of reads assigned to them. Is there something I can adjust to try and avoid this? It seems as if reads are incorrectly assigned to barcodes that are not actually present in the sample.
I ran the pipeline with default settings. Please let me know if I need to provide you with anything more.
Hi,
I ran sicelore 2.1 workflow for my sample. Based on loading concentrations as well as a short-read experiment we performed on the same sample, we expect little over 17 000 unique cell barcodes in our sample. However, when running sicelore, I end up with over 90 000 barcodes. Of course, the large majority of these have only a very low number of reads assigned to them. Is there something I can adjust to try and avoid this? It seems as if reads are incorrectly assigned to barcodes that are not actually present in the sample. I ran the pipeline with default settings. Please let me know if I need to provide you with anything more.
Thanks, Tijs