Access our Data Analysis Report for Microbiome

Our team has created a sample report featuring an analysis of 16S rRNA sequencing data for a study on microbiome. The aim of this report was to compare the microbiomes of celiac disease patients (CeD) to those of first degree relatives of celiac patients (FDR), representing the “pre-disease” state, and healthy controls (DC). Further, samples were compared from duodenal biopsies (disease site) and stool samples (representing whole gut microbiome). 16S rRNA sequencing data was made available by the authors of “Comparison of Small Gut and Whole Gut Microbiota of First-Degree Relatives With Adult Celiac Disease Patients and Controls”, published by Bodkhe et al. in Frontiers in Microbiology (February 2019). Differences between groups (CeD, FDR and DC) and sample origin (biopsy and stool) were evaluated at both the individual species level and at the ecosystem level.

Fios difference

Fios Genomics offers established, cost-efficient and rapid turnaround analysis services for gene expression data from a range of platforms.

Every time our clients work with Fios, they benefit from 

  • A dedicated analyst backed by an experienced team to curate all data, identify the most appropriate statistical approach to take, and provide biological interpretation of results. 
  • An interactive data analysis report, internally peer-reviewed, including all analysis methods and results.  
  • Post-report follow ups: upon receipt of our data analysis report, we arrange a teleconference so that our lead analyst can talk through the results. 
  • Access to large capacity computing and secure data storage facilities. 

Fill out this form to access our

data analysis sample report for Microbiome research

Sample report request - Microbiome
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Contact details

Fios Genomics
BioCube 1
13 Little France Road, Edinburgh BioQuarter
EH16 4UX, Edinburgh
United Kingdom

info@fiosgenomics.com

+44 (0) 131 322 3770

Our expertise

Watch our video where our team of bioinformaticians talk about extracting biological insight from NGS data and the challenges in doing this.

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