<p>Chromosome conformation capture methods, such as Hi-C, have been used to profile chromosome organization from a wide variety of biosamples and conditions; however, existing methods for analyzing such datasets have disadvantages for large-scale integrative studies of long-range interactions. To address this shortcoming, we introduce an analytical framework, <i>jointly-hic,</i> that computes harmonized projections across arbitrarily many contact frequency matrices, suitable for integrative studies of compartmentalization and long-range interactions. Our approach produces robust and directly comparable first and higher-order principal component scores that collectively capture biologically meaningful information beyond traditional A/B compartment scores.</p>

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Jointly-hic: joint decomposition of contact frequency maps captures salient features of genome architecture across tissues and development

  • Thomas Reimonn,
  • Vedat O. Yilmaz,
  • Hoang Tran,
  • Garrett Ng,
  • Derek Liu,
  • Nezar Abdennur

摘要

Chromosome conformation capture methods, such as Hi-C, have been used to profile chromosome organization from a wide variety of biosamples and conditions; however, existing methods for analyzing such datasets have disadvantages for large-scale integrative studies of long-range interactions. To address this shortcoming, we introduce an analytical framework, jointly-hic, that computes harmonized projections across arbitrarily many contact frequency matrices, suitable for integrative studies of compartmentalization and long-range interactions. Our approach produces robust and directly comparable first and higher-order principal component scores that collectively capture biologically meaningful information beyond traditional A/B compartment scores.