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Center for Data and Simulation Science

The development of massively parallel sequencing has fueled genome-centric cancer research. This technology has enabled us to sequence entire cancer genomes and transcriptomes in a relatively short period of time. However, the data produced by this approach is highly complex and difficult to analyze in order to extract the biologically relevant information. The lab of Martin Peifer develops computational methods to analyze and interpret large-scale cancer genome sequencing data. His lab has a special focus on the reconstruction of tumor evolution and on the mechanistic understanding of genome instability. Due to the large size of the data, high performance computing and machine learning plays a central role in their method developments. Martin Peifer is member of the International Cancer Genome Consortium and participant of its Pan-Cancer Analysis of Whole Genomes.

Selected publications

  1. Cun Y, Yang TP, Achter V, Lang U, Peifer M. (2018). Copy number analysis and inference of subclonal populations in cancer genomes using Sclust. Nature Protocols (accepted for publication).
  2. Herling C, Abedpour N,..., Peifer M. (2018). Clonal dynamics towards the development of venetoclax resistance in chronic lymphocytic leukemia. Nature Communications 9, 727.
  3. Peifer M*, Hertwig F,..., Fischer M* (2015). Telomerase activation by genomic rearrangements in high-risk neuroblastoma. Nature 52, 700-4. *corresponding authors
  4. George J,..., Peifer M*, Sage J*, Thomas RK*. (2015) Comprehensive genomic profiling of small cell lung cancer. Nature 524, 47-53. *corresponding authors
  5. Schramm A, Köster J, Assenov Y, Althoff K, Peifer M,..., Schulte JH. (2015) Mutational dynamics between primary and relapse neuroblastomas. Nature Genetics 526, 700-4.
  6. Lu X, Thomas RK, Peifer M. CGARS: cancer genome analysis by rank sums. (2014) Bioinformatics 30, 1295-6.
  7. Fernandez-Cuesta L*, Peifer M*,..., Thomas RK. (2014) Frequent mutations in chromatin-remodelling genes in pulmonary carcinoids. Nature Communications 5, 3518. *equal contribution
  8. The Cancer Genome Atlas Research Network. (2014) Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543-50
  9. The Cancer Genome Atlas Research Network. (2012) Comprehensive genomic characterization of squamous cell lung cancers. Nature 489, 519-25.
  10. Peifer M, ..., Thomas RK. (2012) Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer. Nature Genetics 44, 1104-10.