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DOI: 10.4230/LIPIcs.WABI.2025.11

Mutational Signature Refitting on Sparse Pan-Cancer Data

Authors: Gal Gilad, Teresa M. Przytycka, and Roded Sharan

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract

Mutational processes shape cancer genomes, leaving characteristic marks that are termed signatures. The level of activity of each such process, or its signature exposure, provides important information on the disease, improving patient stratification and the prediction of drug response. Thus, there is growing interest in developing refitting methods that decipher those exposures. Previous work in this domain was unsupervised in nature, employing algebraic decomposition and probabilistic inference methods. Here we provide a supervised approach to the problem of signature refitting and show its superiority over current methods. Our method, SuRe, leverages a neural network model to capture correlations between signature exposures in real data. We show that SuRe outperforms previous methods on sparse mutation data from tumor type specific data sets, as well as pan-cancer data sets, with an increasing advantage as the data become sparser. We further demonstrate its utility in clinical settings.

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Gal Gilad, Teresa M. Przytycka, and Roded Sharan. Mutational Signature Refitting on Sparse Pan-Cancer Data. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 11:1-11:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gilad_et_al:LIPIcs.WABI.2025.11,
  author =	{Gilad, Gal and Przytycka, Teresa M. and Sharan, Roded},
  title =	{{Mutational Signature Refitting on Sparse Pan-Cancer Data}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{11:1--11:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.11},
  URN =		{urn:nbn:de:0030-drops-239374},
  doi =		{10.4230/LIPIcs.WABI.2025.11},
  annote =	{Keywords: mutational signatures, signature refitting, cancer genomics, genomic data analysis, somatic mutations}
}

Document

DOI: 10.4230/LIPIcs.WABI.2018.7

A Dynamic Algorithm for Network Propagation

Authors: Barak Sternberg and Roded Sharan

Published in: LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)

Abstract

Network propagation is a powerful transformation that amplifies signal-to-noise ratio in biological and other data. To date, most of its applications in the biological domain employed standard techniques for its computation that require O(m) time for a network with n vertices and m edges. When applied in a dynamic setting where the network is constantly modified, the cost of these computations becomes prohibitive. Here we study, for the first time in the biological context, the complexity of dynamic algorithms for network propagation. We develop a vertex decremental algorithm that is motivated by various biological applications and can maintain propagation scores over general weights at an amortized cost of O(m/(n^{1/4})) per update. In application to real networks, the dynamic algorithm achieves significant, 50- to 100-fold, speedups over conventional static methods for network propagation, demonstrating its great potential in practice.

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Barak Sternberg and Roded Sharan. A Dynamic Algorithm for Network Propagation. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 7:1-7:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{sternberg_et_al:LIPIcs.WABI.2018.7,
  author =	{Sternberg, Barak and Sharan, Roded},
  title =	{{A Dynamic Algorithm for Network Propagation}},
  booktitle =	{18th International Workshop on Algorithms in Bioinformatics (WABI 2018)},
  pages =	{7:1--7:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-082-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{113},
  editor =	{Parida, Laxmi and Ukkonen, Esko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.7},
  URN =		{urn:nbn:de:0030-drops-93095},
  doi =		{10.4230/LIPIcs.WABI.2018.7},
  annote =	{Keywords: Network propagation, Dynamic graph algorithm, protein-protein interaction network}
}

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Documents authored by Sharan, Roded

Mutational Signature Refitting on Sparse Pan-Cancer Data

Abstract

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A Dynamic Algorithm for Network Propagation

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