Direct full-length RNA sequencing reveals unexpected transcriptome complexity during C. elegans development
High throughput RNA sequencing (RNA-seq) using cDNA has played a key role in delineating transcriptome complexity, including alternative transcription initiation, splicing, polyadenylation and base modification. However, the reads derived from current RNA-seq technologies are usually short and deprived of information on modification during reverse transcription, compromising their potential in defining transcriptome complexity. Here we applied a direct RNA sequencing method with ultra-long reads...
Provenance — who produced it, who reused it
Linked to 2 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.
1 further paper cites this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently