SampleQC: robust multivariate, multi-celltype, multi-sample quality control for single cell data

Quality control (QC) is a critical component of single-cell RNA-seq (scRNA-seq) processing pipelines. Current approaches to QC implicitly assume that datasets are comprised of one celltype, potentially resulting in biased exclusion of rare celltypes. We introduce SampleQC, which robustly fits a Gaussian mixture model across multiple samples, and improves sensitivity and reduces bias compared to current approaches. We show via simulations that SampleQC is less susceptible to exclusion of rarer celltypes. We also demonstrate SampleQC on a complex real dataset (867k cells over 172 samples). SampleQC is general, is implemented in R, and could be applied to other data types.