GSE104193

Bulk human RNA-seq from high-throughput sequencing, profiling expression across the transcriptome. The dataset earns a clean A (100/100): base-call quality is the standout, with 92.8% of bases at Q30 and a mean base quality of 36.4, meaning the great majority of reads are called with high confidence and downstream alignment and quantification will not be limited by sequencing noise — and critically, these are directly measured values (evidence_strength=1), so the grade rests on actual FastQC-style metrics rather than extrapolation. Adapter contamination (0.04%) and N content (0.007%) are negligible, and the 28% duplication rate is unremarkable for RNA-seq, where expression of highly transcribed genes naturally produces duplicate reads, so it should not be mistaken for a library-complexity problem. The one caveat for reuse is that processed expression matrices are not described here — supplementary files are reported only as plain TXT — so confirm the count/normalization format suits your pipeline, but on raw-read quality grounds these data are trustworthy and reusable.