Comprehensive Analyses of 723 Transcriptomes Enhance GWAS Biological Interpretation and Genomic Prediction for Complex Traits in Cattle
In this study, we generated 94 RNA-seq data that were colloced from different tissues in Hereford cow (L1 Dominette 01449) and its relatives. By combining these RNA-seq data with our other data and published data, we uniformly assembled and analyzed a total of 723 transcriptomes from 91 tissues and cell types in cattle, to identify tissue-specific genes with the highest specific expression. We then detected the trait-relevant tissues and cell types, and improved genomic prediction for milk produ...
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