Inferring Allele-Specific Copy Number Aberrations and Tumor Phylogeography from Spatially Resolved Transcriptomics

Cong Ma, Metin Balaban, Jingxian Liu, Siqi Chen, Li Ding, Benjamin J. Raphael

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A key challenge in cancer research is to reconstruct the somatic evolution within a tumor over time and across space. Spatially resolved transcriptomics (SRT) measures gene expression at thousands of spatial locations in a tumor, but does not directly reveal genetic aberrations. We introduce CalicoST, an algorithm to simultaneously infer allele-specific copy number aberrations (CNAs) and a spatial model of tumor evolution from SRT of tumor slices. By modeling CNA-induced perturbations in both total and allele-specific gene expression, CalicoST identifies important types of CNAs - including copy-neutral loss of heterozygosity (CNLOH) and mirrored subclonal CNAs- that are invisible to total copy number analysis. CalicoST achieves high accuracy by modeling both correlations in space with a Hidden Markov Random Field and across genomic segments with a Hidden Markov Model.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 28th Annual International Conference, RECOMB 2024, Proceedings
EditorsJian Ma
PublisherSpringer Science and Business Media Deutschland GmbH
Pages466-469
Number of pages4
ISBN (Print)9781071639887
DOIs
StatePublished - 2024
Event28th International Conference on Research in Computational Molecular Biology, RECOMB 2024 - Cambridge, United States
Duration: Apr 29 2024May 2 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14758 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th International Conference on Research in Computational Molecular Biology, RECOMB 2024
Country/TerritoryUnited States
CityCambridge
Period4/29/245/2/24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • cancer
  • copy number aberrations
  • evolution
  • phylogeography
  • spatially resolved transcriptomics

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