CRCbiome

Colorectal cancer (CRC) symptoms are unspecific – often
emerging when the disease is no longer curable. Screening
reduces CRC mortality, but current screening tests need improvement to be more accurate and less costly and invasive. The overall aim of the CRCbiome study is to discover gut microbiota biomarkers for colorectal cancer screening.

The CRCbiome study have recruited 1640 participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study. From the study participants, we have acquired metagenome data, food frequency and lifestyle questionnaires data. Starting up in 2022, we aim to combine omics data (microbiome, epigenome, transcriptome) with clinical and lifestyle data to improve the understanding of CRC carcinogenesis. To assess biomarker potential for early detection of CRC we need to use computational approaches. We will use our own established pipelines for data analyses. In our bioinformatics toolbox, we have pipelines for profiling metagenomes by taxonomy, gene content/functional potential, MAG generation and virus classification. To ensure reproducible, scalable, and portable analytic procedures, we employ the workflow managers such as Snakemake.

Read more about the project (mn.uio.no)

Tags: Active learning, Data fusion/integration, Databases, Dimensionality reduction, Graph neural networks, Probabilistic programming, Time series, Unsupervised learning, Visualization, Information technology
Published July 4, 2023 9:27 AM - Last modified Oct. 23, 2023 11:37 AM