High-throughput RNA sequencing on circular RNA profiles of human triple-negative breast cancer and adjacent normal tissues
In an attempt to search for metastasis-associated circRNAs, we performed RNA-sequencing on ribosomal RNA-depleted total RNA from three pairs of triple-negative breast cancer (TNBC) and adjacent normal tissues. A computational pipeline based on the anchor alignment of unmapped reads was used to identify circular RNAs. Taken together, 69,815 distinct circRNAs were found in this study and 87% were derived from exons, and the others were derived from introns, intergenic region and 3′ or 5′ UTR, etc....
Provenance — who produced it, who reused it
Linked to 3 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.
2 further papers cite this accession but reuse could not be confirmed.
Deep data QC
80/100 · BStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
The B 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