scCoAnnotate is a Snakemake pipeline for efficient reference-based consensus prediction of cell-types in single-cell RNA sequencing (scRNA-seq) data. Developed by the Kleinman Lab, the pipeline allows users to run multiple annotation tools to predict cell type labels of multiple scRNA-seq samples. The tools consist of several statistical models and machine learning approaches used in the single-cell field. It then outputs a consensus of the predictions, which has been found to increase accuracy in benchmarking experiments by combining the strengths of the different approaches. The automated pipeline is user-friendly and running it does not require knowledge of machine learning. It also features parallelization options to exploit available computational resources for maximal efficiency.