Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms
We introduce an approach to transcript discovery coupled with a statistical model for RNA-Seq experiments that produces estimates of transcript abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation timeseries. We detected 13,689 known transcripts and 3,724 previously unannotated ones, 62% of which ar...
Provenance — who produced it, who reused it
Linked to 5 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.
- Long non-coding RNA Linc-RAM enhances myogenic differentiation b... 2017 · 188 cites
- Recursive splicing in long vertebrate genes 2015 · 172 cites
3 further papers cite 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