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. Author manuscript; available in PMC: 2017 Mar 26.
Published in final edited form as: Nat Neurosci. 2016 Sep 26;19(11):1442–1453. doi: 10.1038/nn.4399

Table 1.

Overlaps and differences between CMC and other publicly available eQTL resources

Comparison cohort eQTL genes compared to CMC
eQTL
Cohort Sample Size Study PMID/GEO
ID/dbGaP ID
Number
of cis
eQTL
Proportion
of non-null
hypotheses
1) in CMC
Unique
Genes
with
eQTL
eQTL Genes
Expressed in
CMC
Genes
with eQTL
in CMC
Genes w/
eQTL in CMC
but not in
comparison
cohort
Blood eQTL 2494 twins 24728292 9640* 0.54 9533 8108 6794 5052
Brain Cloud 108 GSE30272 374223 0.7 6199 5386 4666 7180
Brain Meta-
analysis
424 25290266 3520** 0.62 3503 2806 2507 9339
GTEx PFC 92 25954002 173026 0.98 1922 1326 1284 11853
HBCC 279 phs000979.v1.p1 788338 0.77 7514 6785 5862 7275
HBTRC 146 GSE44772 531400 0.75 6473 5186 4555 7291
NIM 145 GSE15745 105735 0.79 2127 2057 1851 9995
UKBEC 134 25174004 52593 0.93 808 618 546 11300
UNION 1573706 0.7 16568 12644 10544 2593
*

Best eQTL per probeset reported

**

Best eQTL per gene reported

FDR ≤ 5% used to define eQTL in all cohorts. eQTL for Brain Cloud, HBCC, HBTRC, NIH and UKBEC were computed as described in the supplement. eQTL for the Blood cohort, Brain Meta-analysis and GTEx were downloaded from public resources. All eQTL resources represent prefrontal or frontal cortex except the Blood cohort (peripheral blood) and the Brain Meta-analysis (meta-analysis across multiple brain regions). The UNION set was derived by including all unique eQTL from all 8 cohorts.