Deciphering the combinatorial influence of diet and the microbiota on experimental colitis
Background & Aims: The complex interactions between diet and the microbiota that influence mucosal inflammation and inflammatory bowel disease are poorly understood. Experimental colitis models provide the opportunity to control and systematically perturb diet and the microbiota in parallel to quantify the contributions between multiple dietary ingredients and the microbiota on host physiology and colitis. Methods: To examine the interplay of diet and the gut microbiota on host health and col...
Provenance — who produced it, who reused it
Linked to 1 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- Interactions Between Diet and the Intestinal Microbiota Alter In... 2017 · 361 cites
Deep data QC
100/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
Bulk RNA-seq (mouse). Grade A: excellent across all measured metrics (Q30=97.5%, base quality=36.1, duplication=27%), minimal N-content (0.001%), and negligible adapter (0.01%). This is a high-confidence dataset with minimal technical artifacts. Strongly recommended for reuse in all standard RNA-seq analyses.
The A grade is a transparent weighted average. Each metric below scored from 0–100% against the published bulk-RNA-seq thresholds, weighted by its importance; nothing is hidden or subjective.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0