Gut Microbiota Responses to Resistant Starch Across Multiple Dietary Intervention Cohorts

586 paired fecal samples from healthy adults across multiple independent cohorts undergoing resistant starch dietary interventions. The dataset, authored by Biao Dong and last updated in May 2026, analyzes reproducible gut microbial responses and validates findings in inflammatory bowel disease populations. It includes differential abundance analysis, co-occurrence network results, and machine learning classification outcomes.

Use Cases

• Identifying microbial taxa consistently depleted by resistant starch based on differential abundance analysis across cohorts.
• Training machine learning models for cross-cohort discrimination of dietary response based on the reported AUROC of approximately 0.68.
• Investigating the enrichment of specific depleted taxa in Crohn’s disease and ulcerative colitis patients for biomarker discovery.
• Analyzing co-occurrence network structures to understand ecological shifts in the gut microbiome following fiber intervention.

Strengths

• Includes 586 paired fecal samples, providing a substantial sample size for analysis.
• Data is processed through a unified bioinformatics pipeline across multiple independent cohorts, which likely reduces technical variability.
• Findings are validated against eight inflammatory bowel disease cohorts, demonstrating potential clinical relevance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying analysis tables is unknown, which may limit suitability assessment.
• The dataset is very small (14.5 KB), suggesting it may contain summary results or a document rather than raw sequence data.

Provenance

Source

figshare, author Biao Dong.

Collection Method

Gut microbiota composition analysis from fecal samples collected during dietary interventions.

Freshness

Last updated 2026-05-20 05:44:17; freshness should be verified.