gcat, its_a_scam: modular tools for single cell data processing and per-cellquality control
- 1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
Abstract
Motivation: The era of designing bioinformatic pipelines using open source tools is giving way to monolithic, and often proprietary, tools designed for end-to-end analysis, especially in the context of single cell data. While these tools are convenient for going from sequencing data to an almost complete data analysis "in a few clicks", they can strongly limit data use beyond standard analyses Results: We developed Gene and Chromosome Analysis Toolkit (gcat) and It's a scam To Sell Another Single Cell Analysis Method (its_a_scam) for modular processing and quality control of single cell genomic data, freeing users from their reliance on proprietary tools. gcat is a C++ library for parsing genomic data and working with it over genomic coordinates. its_a_scam is built on top of gcat and provides a suite of tools for a wide range of single cell data processing and quality control. its_a_scam can be used in conjunction with commonly used open source tools for scRNA-seq and scATAC-seq count matrix generation, and for performing per-cell quality control directly from alignment files. These alignment-level per-cell metrics can be used for quality control of each cell or to understand celltype differences post-clustering or post-annotation. Using a peripheral blood mononuclear cell Multiome dataset, we show that the count matrices generated with the aid of its_a_scam are highly concordant with those generated by proprietary pipelines. The alignment metrics further demonstrate celltype differences in aligned genomic regions, metagene profiles, and genebody coverage. The modular nature of its_a_scam allows users to integrate it into their existing pipelines, while also enabling analysis beyond current pipelines. Availability: gcat (distributed as gcatlib) and its_a_scam are open source and available at https://github.com/rishvanth-kp/gcatlib and https://github.com/rishvanth-kp/its_a_scam. Detailed documentation is available at https://gcatlib.readthedocs.io/ and https://its-a-scam.readthedocs.io.
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BibTeX
@misc{prabakar2026gcat,
title = {{gcat, its_a_scam: modular tools for single cell data processing and per-cellquality control}},
author = {R. K. Prabakar and H. V. Meyer},
howpublished = {bioRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.03.764034},
url = {https://www.biorxiv.org/content/10.64898/2026.11.03.764034v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - gcat, its_a_scam: modular tools for single cell data processing and per-cellquality control
AU - R. K. Prabakar
AU - H. V. Meyer
PY - 2026
DA - 2026/11/03
PB - bioRxiv
DO - 10.64898/2026.11.03.764034
UR - https://www.biorxiv.org/content/10.64898/2026.11.03.764034v1
AB - Motivation: The era of designing bioinformatic pipelines using open source tools is giving way to monolithic, and often proprietary, tools designed for end-to-end analysis, especially in the context of single cell data. While these tools are convenient for going from sequencing data to an almost complete data analysis "in a few clicks", they can strongly limit data use beyond standard analyses Results: We developed Gene and Chromosome Analysis Toolkit (gcat) and It's a scam To Sell Another Single Cell Analysis Method (its_a_scam) for modular processing and quality control of single cell genomic data, freeing users from their reliance on proprietary tools. gcat is a C++ library for parsing genomic data and working with it over genomic coordinates. its_a_scam is built on top of gcat and provides a suite of tools for a wide range of single cell data processing and quality control. its_a_scam can be used in conjunction with commonly used open source tools for scRNA-seq and scATAC-seq count matrix generation, and for performing per-cell quality control directly from alignment files. These alignment-level per-cell metrics can be used for quality control of each cell or to understand celltype differences post-clustering or post-annotation. Using a peripheral blood mononuclear cell Multiome dataset, we show that the count matrices generated with the aid of its_a_scam are highly concordant with those generated by proprietary pipelines. The alignment metrics further demonstrate celltype differences in aligned genomic regions, metagene profiles, and genebody coverage. The modular nature of its_a_scam allows users to integrate it into their existing pipelines, while also enabling analysis beyond current pipelines. Availability: gcat (distributed as gcatlib) and its_a_scam are open source and available at https://github.com/rishvanth-kp/gcatlib and https://github.com/rishvanth-kp/its_a_scam. Detailed documentation is available at https://gcatlib.readthedocs.io/ and https://its-a-scam.readthedocs.io.
ER -