We are a computational research group at the Institute for Computational Cancer Biology Cologne (ICCB) at the University of Cologne and the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at the TU Berlin.
Our lab develops and applies algorithms and computational methods to understand how cellular and intra-tumour heterogeneity (ITH) arises and how it affects tissue and patient phenotypes in space and time. We are particularly interested in chromosomal instability (CIN) and somatic copy-number alterations (SCNA), a key characteristic that separates cancerous from healthy somatic tissue. In our methods we leverage statistical and machine learning approaches as well as classical computer science algorithms and simulations and develop these models in close collaboration with our experimental partners.
Specifically, we are active in three research areas:
- Structural evolution of cancer genomes, where we conduct retrospective studies to infer cancer evolution from clinical patient samples and forward simulations that enable us to investigate cancer growth and evolution in-silico
- Interpretation of genetic variation, where we leverage machine learning and statistical genetics approaches on large cohorts to understand cancer gene regulation and epigenetics
- Early detection and prevention, where we work on population-based molecular biomarkers and patient risk stratification.
Our work bridges theoretical and applied biomedical research and we develop, train, and validate our methods on large clinical datasets as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG), ICGC-ARGO, and the TRACERx Consortium as well as several smaller consortia.
Our main location is at the University Hospital Cologne in the vibrant, international city of Cologne, Germany.
We are also maintaining a branch at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) in the German capital of Berlin.
Keep an eye on our recruitment page for job openings at either location.
Eight years after its intial release we are more than proud to announce that the MEDICC2 algorithm and paper for inferring cancer evolution from somatic copy-number alterations is now published online at Genome Biology.
MEDICC2 is the leading algorithm for phylogenetic reconstruction from and quantification of chromosomal instability. It is based on an efficient finite-state transducer framework which, together with integrated parallelisations, allows accurate phylogentic inference even for single-cell data with thousands of cells.
MEDICC2 not only outperforms the original implementation in speed by orders of magnitude, but also, as the first and only algorithm in the field, allows the accurate detection of clonal and subclonal whole-genome doubling events.
The Schwarzlab is welcoming several new members to our group at our site in Cologne at the ICCB!
Daniel Schütte is a clinician scientist who is interested in molecular biomarkers and cancer early detection and prevention and already joined some months ago.
Felix Schifferdecker and Selina Wächter are two MD students who will be writing their dissertation in the lab in parallel to their MD coursework and clinical pratice over the next years. Felix will be working on simulating chromosomal aberrations in cancer evolution and Selina will be investigating methods for detecting selection in cancer phylogenies.
Finally, we would like to welcome Teodora Bucaciuc, who has joined the lab as a research associate, developing pipelines for copy-number analysis and investigating the co-evolution of genomic and epignomic alterations in cancer. Welcome all, great to have you on board!
We are incredibly thrilled that Julia Markowski successfully defended her PhD on October 21, 2022 at the Berlin Institute for Molecular Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association.
Her PhD thesis is titled "Inferring haplotype-specific chromatin conformation using Genome Architecture Mapping" and she will receive her PhD from the Humboldt University Berlin in the near future.
After completing her Masters degree in Bioinformatics at the Max-Planck-Institute for Molecular Genetics and the University of Potsdam, Julia joined our lab in May 2017 on a MDC PhD Fellowship. She was subsequently supported by the DFG priority programme SPP2202 "Chromatin Architecture in Health and Disease".
She is now moving to Boston as a postdoctoral fellow in the Park Lab at Harvard Medical School and we wish her all the best for the future!
Kaufmann T, Petkovic M, Watkins TBK, ..., Van Loo P, Haase K, Tarabichi M, Schwarz RF. MEDICC2: whole-genome doubling-aware copy number phylogenies for cancer evolution. Genome Biology (2022).
▶ MEDICC2 is the leading method for inferring cancer evolution from somatic copy-number alterations. It identifies individual evolutionary events and detects whole-genome doubling. Published only eight years after MEDICC! Second best acronym ever.
Markowski J, Kempfer R, ... , Kehr B, Pombo A, Rahmann S, Schwarz RF. GAMIBHEAR: whole-genome haplotype reconstruction from Genome Architecture Mapping data. Bioinformatics (2021).
▶ GAMIBHEAR is a novel algorithm for inferring chromosome-spanning haplotypes from Genome Architecture Mapping data. It provides the basis for accurate haplotype-specific chromatin contact maps in human. Best acronym ever.
PCAWG Transcriptome Core Group, Calabrese C, Davidson NR, Demircioğlu D, Fonseca NA, He Y, Kahles A, ...,
Brazma A*, Brooks A*, Göke J*, Rätsch G*, Schwarz RF*, Stegle O*, Zhang Z*. Genomic basis for RNA alterations in cancer. Nature (2020).
▶ In the PCAWG consortium we investigated the allele-specific effects of somatic mutations on gene expression as part of PCAWG Working Group 3. Another interesting acronym story.
Watkins TBK, Lim EL, Petkovic M, Elizalde S, Birkbak NJ, Wilson GA, Moore DA, ..., Schwarz RF*, McGranahan N*,
Swanton C*. Pervasive chromosomal instability and karyotype order in tumour evolution. Nature (2020).
▶ In this seminal paper we used the reference phasing algorithm we developed to detect parallel evolution across human cancers in the largest multi-region sequencing dataset to date. Go refphase!
Jamal-Hanjani M, Wilson GA, McGranahan N, Birkbak NJ, Watkins TBK, Veeriah S, Shafi S, ..., Schwarz RF, et al.
Tracking the Evolution of Non–Small-Cell Lung Cancer. N. Engl. J. Med., 376(22):2109–2121 (2017).
▶ In this work, we developed and contributed the reference phasing algorithm to the TRACERx consortium, which lead to the detection of mirrored subclonal allelic imbalance events (MSAI). #notmyacronym
Prof. Dr. Roland F. Schwarz
Computer scientist by training. Lover of formal grammars, Markov models and phylogenetic trees.
Quote: "What if it's a Markov chain?"
Postdoc / Scientific Programmer
Dr. Adam Streck
Computer scientist by training. Modelling the world through cellular automata and stochastic processes. Gamer at heart, living the VR hype. Author of SMITH. Master of Technology.
Dr. Daniel Schütte
Medical doctor and computer scientist. Improving patient care through early detection and better stratification.
Biomathematician. Fond of single-cell data analysis and extrachromosomal DNA. Master of Journal Club.
Quote: "No, Roland, you cannot skip Journal Club."
Tom L. Kaufmann
Physicist by training. Fan of deep learning and mutational processes shaping copy number. Developer of MEDICC2 and refphase. Master of Lab Meeting.
Quotes: "Oups.", "This is funny..."
Victoria M. Dombrowe
Knower of Molecular Medicine. Now mapping the epigenome and its evolution. Master of Events.
Medical student and computer scientist. Simulating cancer evolution and structural alterations.
Medical student. Learning how to code, getting into Bioinformatics.
Biologist and Bioinformatician by training. Interested in genomics and the co-evolution of genome and epigenome.
Dr. Tom Watkins
Physician by training. Chromosomal instability and somatic copy-number alterations.
From the Swanton lab, Francis Crick Institute.
Fierce winged unicorn. Destroyer of bugs. Defender of students. Do not mess with Quark.
Quote: "No, I'm not a pegacorn."
CRUK - TRACERx
We are part of the CRUK funded TRACERx consortium lead by Charles Swanton at the Francis Crick Institute in London where we contribute algorithms for phasing of copy-number alterations and phylogenetic tree inference.
ICGC - ARGO
In ICGC-ARGO we are part of the data coordination and management group and are leading a project that contributes pipelines for allele-specific expression analysis.