Extended Data Fig. 2: Comparison of EM to Patch-seq features, classifier performance, and predicted MET-subclass relative to connectivity-defined subclass.

a) Features of all inhibitory Patch-seq (PS) (n = 477) versus all inhibitory EM neurons (columnar sample + curated MCs n = 173). Boxplot whiskers indicate the range (max/min) of the data. Features are presented by decreasing Gini index as used by the classifier to predict MET-type identity. b) Cumulative histogram for reliability metric. Patch-seq cells which are correctly predicted with their known MET-type are labeled as “Correct MET prediction” and Patch-seq cells which the classifier incorrectly identifies are labeled as “Incorrect MET prediction”. An inset is provided to clearly show where the reliability threshold is defined. c) Confusion matrix for connectivity-defined subclass (labels from Schneider-Mizell.³³) versus predicted MET subclass for EM cells from the columnar sample (n = 163) (frequencies are normalized within subclass). Connectivity-defined targeting labels: Perisomatic targeting cells (PTC) target soma or proximal dendrites, distal dendrite targeting cells (DTC) primarily target apical and/or distal dendrites, sparsely targeting cells (STC) have relatively sparse multisynaptic connections, and inhibitory targeting cells (ITC) target other inhibitory neurons. These subclass definitions correspond to “coarse classical or molecular subclasses…but there is not a one-to-one match”³³. Here they provide a useful benchmark for molecular subclass predictions derived from the Patch-seq classifier. For perspective on the Sst MET-type mapping of column neurons, morphologies are presented by predicted MET-type in Extended Data Fig. 4.