North American Brain Expression Consortium and UK Human Brain Expression Database: Gene Expression
A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the larges...
Provenance — who produced it, who reused it
Linked to 13 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.
- Variation among intact tissue samples reveals the core transcrip... 2018 · 209 cites
- Large Scale Gene Expression Meta-Analysis Reveals Tissue-Specifi... 2016 · 156 cites
- Distinct longevity mechanisms across and within species and thei... 2023 · 149 cites
- Integration of GWAS SNPs and tissue specific expression profilin... 2012 · 143 cites
- Genetic architecture of epigenetic and neuronal ageing rates in... 2017 · 134 cites
- Integrative genomics approach identifies conserved transcriptomi... 2020 · 83 cites
- Age-associated changes in gene expression in human brain and iso... 2012 · 76 cites
6 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
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently