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Sci Data. 2019 Jul 5;6(1):116. doi: 10.1038/s41597-019-0117-3.

Metagenomics and transcriptomics data from human colorectal cancer.

Author information

1
School of Natural and Computational Sciences, Massey University, Auckland, New Zealand. tina.visnovska@rr-research.no.
2
Bioinformatics Core Facility, Oslo University Hospital Radium, Oslo, Norway. tina.visnovska@rr-research.no.
3
School of Fundamental Sciences, Massey University, Palmerston North, New Zealand.
4
School of Natural and Computational Sciences, Massey University, Auckland, New Zealand.
5
Department of Surgery, University of Otago, Christchurch, New Zealand.

Abstract

Colorectal cancer is a heterogenous and mostly sporadic disease, the development of which is associated with microbial dysbiosis. Recent advances in subtype classification have successfully stratified the disease using molecular profiling. To understand potential relationships between molecular mechanisms differentiating the subtypes of colorectal cancer and composition of gut microbial community, we classified a set of 34 tumour samples into molecular subtypes using RNA-sequencing gene expression profiles and determined relative abundances of bacterial taxonomic groups. To identify bacterial community composition, 16S rRNA amplicon metabarcoding was used as well as whole genome metagenomics of the non-human part of RNA-sequencing data. The generated data expands the collection of the data sources related to the disease and connects molecular aspects of the cancer with environmental impact of microbial community.

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