Correcting Chimeric Crosstalk in Single Cell RNA-seq Experiments

Abstract

As part of the process of preparing sequencing libraries that include unique molecular identifiers (UMIs) such as many single cell RNA-seq (scRNA-seq) libraries, a diverse template must be amplified. During amplification, spurious chimeric molecules can be formed between molecules originating in different cells. While several computational and experimental strategies have been suggested to mitigate the impact of chimeric molecules, suitable approaches for scRNA-seq experiments do not exist. We demonstrate that chimeras become increasingly problematic as samples are sequenced deeply and propose both supervised and unsupervised computational solutions. These solutions are validated in the context of a deeply sequenced species mixing experiment, and, orthogonally, using replicate PCR amplifications of the same scRNA-seq library. Our code is publicly available at https://github.com/asncd/schimera.