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. Author manuscript; available in PMC: 2015 Jul 2.
Published in final edited form as: Neuron. 2014 Jul 2;83(1):69–86. doi: 10.1016/j.neuron.2014.05.035

Figure 4.

Figure 4

CoNTExT predicts developmental period and regional identity in individual phNPC cultures. (A) The CoNTExT algorithm was trained on all samples from a spatio-temporal atlas of human brain expression (Kang et al., 2011) (1340 samples using Affymetrix Exon 1.0 ST Array), and validated in several post-mortem expression datasets. Probability (color in heat map) of each predicted class assignment (y-axis) is shown for each sample of known regional and temporal identity (x-axis). (B) Cross platform accuracy was evaluated in 49 samples spanning all postnatal developmental periods and both cerebellar and cortical regions (Liu et al., 2012) (Affymetrix Gene 1.0 ST Array). Developmental period was classified with 84% (+/− one period) and 100% accuracy in region. (C) The validated machine learning algorithm was applied to one line (Donor: 8 Region: 49) of differentiating phNPCs to predict developmental period and regional identity (Illumina HT-12 Beadchip). A clear maturation across differentiation weeks is seen at the individual sample level, with the culture reaching early to late fetal periods of development. In addition, the cultures are predicted to be cortical, consistent with immunocytochemical profile and expression of regional markers.