Fig. 1: Schematic of the BENGAL pipeline.

1 Quality control of input data is performed prior to data integration. and is not part of BENGAL. Potential doublets and low-quality cells expressing high mitochondrial genes should be removed. Cell ontology annotations are collected from atlases or data portals or curated from the originally published annotation. 2 When the granularity of ontology annotation is incomparable across datasets, one-to-one homology between cell types needs to be robustly aligned. We developed scOntoMatch to find the appropriate annotation granularity and align cell type hierarchies across given datasets (see Methods). 3 Genes are grouped and translated across species by homology defined in ENSEMBL multiple species comparison tool. Raw count matrices are then concatenated across species using four possible homology matching methods respective to method inputs. 4 Run 9 integration algorithms to generate integrated output. 5 Perform integration assessment from species mixing, biology conservation and cell type annotation transfer. BENGAL, BENchmarking strateGies for cross-species integrAtion of singLe-cell RNA sequencing data; QC, quality control; MT, mitochondrial; SCCAF, single cell clustering assessment framework; AUC, area under the curve; CV, cross-validation. Created with BioRender.com.