We found that individual ICs corresponded to recognizable biological phenomena (Figure 1D and Figure S2C–H)(Adamson et al., 2016), in contrast to results from principal components analysis (Figure S2A). For example, among glutamatergic neurons from frontal cortex cluster 6, we identified ICs whose strongly loading genes marked specific cell types, cell states or spatial gradients across anatomical axes (Figure 1D). Other ICs captured technical effects such as 1) cells from different replicate preparations; 2) RNA libraries of different sizes; 3) experimentally identified effects of tissue preparation; or 4) cell-cell “doublets” (Figure S2C-H). We found that the interpretability of individual ICs allowed us to distinguish presumed endogenous signals (called “biological ICs”) from ICs related to the technical signals described above. Removing technical ICs reduced spurious distinctions among cells (Figure S2I).
