The Lindbjerg group's research is centered around colorectal cancer (CRC) both it's biology and clinical translation of findings.

Claus Lindbjerg Andersen at Google Scholar

About Colorectal Cancer

CRC is one of the most common cancers in the world, with over 5000 new cases in Denmark each year. Despite most patients being offered treatment with curative intent, a large proportion of patients experience disease recurrence or death from CRC.


Our research mainly revolves around biomarker discovery and validation, with the aim to develop clinically implementable prognostic and predictive biomarkers.

We generate and work with extensive genomic, epigenomic, transcriptomic, and proteomic data to discover prognostic CRC subtypes and explore the biology behind CRC.

Research hallmarks for colorectal cancer in the Lindbjerg group © Tenna V. Henriksen 2022

circulating tumor DNA

Additionally, we investigate the use of circulating tumor DNA (ctDNA) as a biomarker both for early detection of CRC (screening) as well as peri- and post-treatment monitoring of the disease.
To this end, we are highly involved in the  Danish National Center for Circulating TumorDNA Guided Cancer Treatment and are running several large clinical trials. Moreover, we have a strong technological focus on developing new methods for ctDNA detection, both in the lab and bioinformatically.

Epidemiology of ColOrectal Cancer

In combination with our molecular research, we carry out epidemiological research on large national registry datasets to further uncover clinical challenges in CRC management. We have the privilege of working with clinical patient material and data, in close collaboration with the treating surgeons, oncologists and nurses. The end goal for all our studies remains improving the lives for patients with colorectal cancer globally.


NormFinder is an algorithm for identifying the optimal normalization gene among a set of candidates.

Infer iRNA expression scores for 11 cancer types

R package for Circulating Tumor DNA Detection by Droplet Digital PCR

Deep Read-level Error Model for Sequencing data. Includes modules for ctDNA variant calling and cancer detection (2022)

Group leader

Claus Lindbjerg Andersen

Professor, PhD, MSc, Group leader