gcat, its_a_scam: modular tools for single cell data processing and per-cellquality control

In a peripheral blood mononuclear cell Multiome dataset, count matrices produced with its_a_scam are highly concordant with those from proprietary pipelines, supporting alignment-based single-cell QC.

• Why it matters: Proprietary end-to-end single-cell tools can restrict reuse beyond standard analyses, creating a need for modular, open-source processing and per-cell quality control.
• What they did: The authors built gcat as a C++ library for genomic-coordinate parsing and used it to create its_a_scam, which generates per-cell QC metrics directly from alignment files.
• The result: Alignment-derived metrics reveal celltype differences in aligned regions, metagene profiles, and genebody coverage, enabling QC per cell and downstream biological comparisons.

AI summary of the abstract · may contain errors · not medical advice · read the paper.