Tumour Heterogenity & Evolution

This module investigates the impact and association of clonal diversity and evolution on clinical correlates in cancer. Through development of robust statistical models of phylogenetic progression and population re-construction from next generation sequencing data, informative quantitative attributes of cancers relating to temporal and spatial dynamics can be computing. These will be applied in the context of the large scale resource of the collaboratory for investigation of the evolutionary determinants of clinical progression at scale.

Research Statement

  1. Develop a suite of software implementing a novel statistical models for evolutionary inference from whole genome sequencing data from tumours.
  2. Utilize an unprecedented evolutionary profiling of thousands of tumour samples to investigate the relationship between clonal evolution and clinical outcomes across tumour types.
  • Management Team

  • Development Team

    • Sohrab Salehi, PhD Cand
    • Fatemeh Dorri, PhD Cand
    • Andrew McPherson, PDF
    • Jafar Taghiyar, Software Developer
  • Collaborators

    • Alexandre Bouchard-Cote, Collaborator


The evolution of tumours is thought to be a major determinant of the tumour aggressiveness and response to therapy. By developing tools that can reconstruct the evolution of individual tumours and by using these tools to relate tumour heterogeneity to clinical behavior, we set the stage for tumour evolution-aware design of customized therapies for cancer patients.


  • Software

    All software available at the Shah Lab for Computational Cancer Biology

Latest Publications & Presentations


Roth A, McPherson A, Laks E, Biele J, Yap D, Wan A, Smith MA, Nielsen CB, McAlpine JN, Aparicio S, Bouchard-Côté A, Shah SP, (2016)

Clonal genotype and population structure inference from single-cell tumor sequencing.

Nature methods, 2016;13(7):573-6


McPherson A, Roth A, Laks E, Masud T, Bashashati A, Zhang AW, Ha G, Biele J, Yap D, Wan A, Prentice LM, Khattra J, Smith MA, Nielsen CB, Mullaly SC, Kalloger S, Karnezis A, Shumansky K, Siu C, Rosner J, Chan HL, Ho J, Melnyk N, Senz J, Yang W, Moore R, Mungall AJ, Marra MA, Bouchard-Côté A, Gilks CB, Huntsman DG, McAlpine JN, Aparicio S, Shah SP, (2016)

Divergent modes of clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer.

Nature genetics, 2016;48(7):758-67


Eirew P, Steif A, Khattra J, Ha G, Yap D, Farahani H, Gelmon K, Chia S, Mar C, Wan A, Laks E, Biele J, Shumansky K, Rosner J, McPherson A, Nielsen C, Roth AJ, Lefebvre C, Bashashati A, de Souza C, Siu C, Aniba R, Brimhall J, Oloumi A, Osako T, Bruna A, Sandoval JL, Algara T, Greenwood W, Leung K, Cheng H, Xue H, Wang Y, Lin D, Mungall AJ, Moore R, Zhao Y, Lorette J, Nguyen L, Huntsman D, Eaves CJ, Hansen C, Marra MA, Caldas C, Shah SP, Aparicio S, (2015)

Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution.

Nature, 2015;518(7539):422-6