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Differences in Gut Microbial Composition correlate with Regional Brain Volumes in Irritable Bowel Syndrome

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Dataset overview

Participants 52
Samples 52
Reuse readiness 7.7/10 evidence-backed score

tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data.

Ostner J, Carcy S, Müller CL. · Frontiers in genetics · 2021

Abstract

Accurate generative statistical modeling of count data is of critical relevance for the analysis of biological datasets from high-throughput sequencing technologies. Important instances include the modeling of microbiome compositions from amplicon sequencing surveys and the analysis of cell type compositions derived from single-cell RNA sequencing. Microbial and cell type abundance data share remarkably similar statistical features, including their inherent compositionality and a natural hierarchical ordering of the individual components from taxonomic or cell lineage tree information, respectively. To this end, we introduce a Bayesian model for <b>t</b>ree-aggregated <b>a</b>mplicon and <b>s</b>ingle-<b>c</b>ell <b>co</b>mpositional <b>d</b>ata <b>a</b>nalysis (tascCODA) that seamlessly integrates hierarchical information and experimental covariate data into the generative modeling of compositional count data. By combining latent parameters based on the tree structure with spike-and-slab Lasso penalization, tascCODA can determine covariate effects across different levels of the population hierarchy in a data-driven parsimonious way. In the context of differential abundance testing, we validate tascCODA's excellent performance on a comprehensive set of synthetic benchmark scenarios. Our analyses on human single-cell RNA-seq data from ulcerative colitis patients and amplicon data from patients with irritable bowel syndrome, respectively, identified aggregated cell type and taxon compositional changes that were more predictive and parsimonious than those proposed by other schemes. We posit that tascCODA constitutes a valuable addition to the growing statistical toolbox for generative modeling and analysis of compositional changes in microbial or cell population data.

doi:10.3389/fgene.2021.766405 ↗ PMID 34950190 ↗ PMC8689185 ↗

Study facts

Organism
human gut metagenome
Platform
454 GS FLX Titanium
Age group
adult
Disease groups
Non-IBD controls
Anatomical sites
—

Data availability

  • Analysis code

Strengths & limitations for reuse

Strengths

  • Raw reads are advertised
  • Feature/OTU tables are advertised
  • Taxonomic tables are advertised
  • Analysis code is available
  • Participant counts are documented
  • Sample counts are documented
Extraction evidence & provenance

Each extracted field is shown with the source excerpt and location used to resolve it.

Assay

FieldValueEvidence
assay.platform 454 GS FLX Titanium from source
ENA instrument_model=454 GS FLX Titanium

Section ENA study report, offset —
assay.sequencing_type amplicon_16s
16S rRNA gene sequencing (V3-V5 region, 454 platform) was used to characterize stool microbial communities

Section study.description, offset 350
assay.target_region V3-V5
16S rRNA gene sequencing (V3-V5 region, 454 platform)

Section study.description, offset 350

Cohort

FieldValueEvidence
cohort.age_group adult
stool samples and structural brain images were collected from 30 adult IBS and 23 healthy control subjects

Section study.description, offset 250
cohort.non_ibd_controls 23
23 healthy controls

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 45000
cohort.total_participants 52
The dataset consists of n = 52 samples, with 23 healthy controls, and 29 IBS patients

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 45000

Data_Assets

FieldValueEvidence
data_assets.analysis_code True
The scripts used for data analysis and benchmark data generation can be found in the tascCODA reproducibility repository

Section Data availability, offset 70000
data_assets.feature_or_otu_table True
yielding a final count table with 709 ASVs

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 45700
data_assets.open_access True
The datasets used in this study are publicly available ... PRJNA373876

Section Data availability, offset 69800
data_assets.pipeline_or_tool_versions True
DADA2, version 1.21.0 ... Silva database, version 138.1

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 45600
data_assets.raw_reads True
We re-processed the raw 16S rRNA sequences with DADA2

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 45500
data_assets.sample_metadata True
metadata information about age, sex and BMI of most subjects is available

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 45900
data_assets.taxonomic_table True
did taxonomic assignment via the Silva database, version 138.1

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 45600

Specimens

FieldValueEvidence
specimens.body_site gut
differences in gut microbial composition

Section study.description, offset 170
specimens.number_of_samples 52 from source
ENA sample_count=52

Section ENA study report, offset —
specimens.sample_type stool
we analyzed 16S rRNA sequencing data of stool samples collected from IBS patients and healthy controls

Section 3.2.2 Analysis of the Human Gut Microbiome Under Irritable Bowel Syndrome, offset 44800