scAmp analyzes focal gene amplifications at single-cell resolution

Jones, M. G.; Weiser, N. E.; Hung, K. L.; Yan, X.; Agarwal, S.; Luebeck, J.; Gnanasekar, A.; Howitt, B. E.; Curtis, E. J.; Yu, K.; Rose, J. C.; Kraft, K.; Amiri, V. V. P.; Satpathy, L.; Bafna, V.; Mischel, P. S.; Chang, H. Y.

doi:10.64898/2026.02.14.705928

bioRxiv · 10.64898/2026.02.14.705928

scAmp analyzes focal gene amplifications at single-cell resolution

Jones, M. G.·Weiser, N. E.·Hung, K. L.·Yan, X.·Agarwal, S.·Luebeck, J.·Gnanasekar, A.·Howitt, B. E.·Curtis, E. J.·Yu, K.·Rose, J. C.·Kraft, K.·Amiri, V. V. P.·Satpathy, L.·Bafna, V.·Mischel, P. S.·Chang, H. Y.

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Abstract

Oncogene amplification on extrachromosomal DNA (ecDNA) is a common driver of tumor progression and is associated with acquired drug resistance and poor patient survival. While whole genome sequencing (WGS) studies have revealed the landscape of genes amplified on ecDNA in tumors, it remains challenging to study the subclonal heterogeneity and functional (e.g., transcriptomic) consequences of ecDNA on tumors. To address this, we introduce scAmp: a probabilistic algorithm for detecting and analyzing ecDNA from single-cell datasets. We demonstrate scAmps improved accuracy over WGS approaches on well-characterized cell-lines and its applicability to clinical histopathology. We further showcase scAmp by analyzing 73 patient tumors profiled with single-cell ATAC-seq, where we analyze the subclonal evolution of ecDNA+ subclones and identify the effect of ecDNA amplifications on the chromatin accessibility landscape of cancer cells. Together, we anticipate that scAmp will broadly enable further studies - both retrospective and prospective - that dissect critical questions of how ecDNA affect cancer cells and the tumors in which they reside.

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Jones, M. G., Weiser, N. E., Hung, K. L., Yan, X., Agarwal, S., Luebeck, J., Gnanasekar, A., Howitt, B. E., Curtis, E. J., Yu, K., Rose, J. C., Kraft, K., Amiri, V. V. P., Satpathy, L., Bafna, V., Mischel, P. S., Chang, H. Y.. 2026-02-15. scAmp analyzes focal gene amplifications at single-cell resolution. https://doi.org/10.64898/2026.02.14.705928

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