Defining the consequences of genetic variation on a proteome-wide scale
Genetic variation governs protein expression through both transcriptional and post-transcriptional processes. To investigate this relationship, we combined a multiplexed, mass spectrometry-based method for protein quantification with an emerging mouse model harboring extensive genetic variation from 8 founder strains. We collected genome-wide mRNA and protein profiling measurements to link genetic variation to protein expression differences in livers from 192 Diversity Outcross mice.
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.
- Defining the consequences of genetic variation on a proteome-wid... 2016 · 429 cites
4 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