RNA-seq analysis of MPCs treated with FGF1 variants
RNA-seq is a powerful tool to analyze differential expression of cellular pathways under different conditions. The goal of this study is to analyze the potential pathways involved in cellular defense against high glucose challenge with or without FGF1 intervention.
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.
Deep data QC
100/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This murine bulk RNA-seq dataset exhibits high read quality (95.7% Q30, 98.5% Q20) with 150.8 bp reads and negligible N content, indicating clean library preparation and sequencing. No adapter contamination detected, suggesting minimal post-sequence processing artifacts. While the specific sequencing instrument is not recorded, the quality metrics indicate suitability for transcript quantification and expression profiling in mouse models.
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