Extended Data Fig. 2: Performance of machine learning model for macaque imGCs and feature extraction and comparison of gene weights defining imGCs in different species. | Nature Neuroscience

Extended Data Fig. 2: Performance of machine learning model for macaque imGCs and feature extraction and comparison of gene weights defining imGCs in different species.

From: Cross-species analysis of adult hippocampal neurogenesis reveals human-specific gene expression but convergent biological processes

Extended Data Fig. 2

a, Measuring performance of our machine learning model for macaque datasets. Line plot showing the accuracy score of the machine learning classifier varying with decreasing regularization strength as estimated by cross-validation. The red line shows a 95% confidence interval on the estimation of the accuracy score. #Sum abs (coeffs): sum of the absolute value of regression coefficients. b, Heatmap showing expression of top gene weights in top-scoring cells of each prototype determined by our machine learning model for macaque datasets. The genes listed are the top 25 weights defining macaque imGCs. c, Venn diagram of the positive gene weights defining imGCs in humans, macaques, and mice that were generated by separate machine learning models (weights for human and mouse imGCs were generated in ref. 25). Schematics in c created using BioRender.com. Astro: astrocyte; OPC: oligodendrocyte progenitor cell; mOli: mature oligodendrocyte.

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