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. Author manuscript; available in PMC: 2016 Oct 1.
Published in final edited form as: J Comp Neurol. 2015 Jul 14;523(14):2043–2061. doi: 10.1002/cne.23777

Table 3.

Results of the CVAs.

Species assignment Region assignment Layer assignment (only cortical regions)
CV1 CV1 CV2 CV3 CV4 CV1 CV2
Weight of linear determinant 100.0% 81.7% 11.1% 4.6% 2.6% 68.5% 31.5%
Coefficients of linear discriminants:
COX5B 9.3 14.1 4.4 3.4 4.1 −4.8 7.0
COX6A1 −2.2 −10.8 −2.1 0.3 −0.1 7.1 −0.2
COX7A2 2.9 −0.5 1.8 −2.8 −1.9 −1.7 −0.8
COX7C −0.7 0.2 −0.7 0.0 0.5 −0.1 0.4
NDUFA4 0.9 6.1 3.9 0.0 −1.2 −5.1 −3.3
NDUFS5 −4.9 12.5 −7.4 −2.0 0.2 −9.6 −0.6
UQCRH 0.5 1.4 0.7 −1.6 −0.8 −1.7 0.3
HBA1 0.6 0.3 0.1 0.1 −0.2 −0.1 −0.1
UBA52 −0.2 −0.1 −0.1 0.0 0.1 0.1 0.1
FKBP1A −11.0 −14.1 −12.2 4.2 4.7 14.3 8.0
PPIA −2.5 −11.1 18.4 −21.7 −2.3 −11.6 −3.8
SKP1 −4.3 3.6 −7.5 3.1 3.1 2.3 6.9
PMS2P3 12.7 −27.5 25.4 −9.6 −13.5 0.0 −30.6
PEBP1 −0.3 −29.7 8.9 1.1 −5.1 15.8 −12.6
SF3B5 1.7 0.4 1.8 −3.1 −2.2 −2.3 −0.9
MYL6B −5.1 −10.7 −3.1 7.1 2.0 12.8 3.7
MIF 2.0 −6.2 0.4 2.1 −0.8 3.9 −4.6
NPY (CPON) −0.1 3.4 −3.3 2.4 1.1 0.4 1.9

The first analysis included all regions of interest and was used to predict the species based upon protein expression. The second analysis included all regions of interest and was used to predict the area of the brain from which the samples originated. The third analysis included only cortical regions and was used to predict the layer of cortex from which the sample originated. The results of each analysis predicted species, region, or neocortical layer assignment with 100% posterior probability.