Using RNA-Seq to create sample-specific proteomic databases that enable mass spectrometric discovery of splice junction peptides
Many new alternative splice forms have been detected at the transcript level using next generation sequencing (NGS) methods, especially RNA-Seq, but it is not known how many of these transcripts are being translated. Leveraging the unprecedented capabilities of NGS, we collected RNA-Seq and proteomics data from the same cell population (Jurkat cells) and created a bioinformatics pipeline that builds customized databases for the discovery of novel splice-junction peptides. Results: Eighty millio...
Provenance — who produced it, who reused it
Linked to 9 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.
- Single-cell TCRseq: paired recovery of entire T-cell alpha and b... 2016 · 147 cites
- Discovery and Mass Spectrometric Analysis of Novel Splice-juncti... 2013 · 134 cites
7 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
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.