In recent years, many software packages for identifying structural variants (SVs) using whole-genome sequencing data have been released. When published, a new method is commonly compared with those already available, but this tends to be selective and incomplete. The lack of comprehensive benchmarking of methods presents challenges for users in selecting methods and for developers in understanding algorithm behaviours and limitations. Here we report the comprehensive evaluation of 10 SV callers, selected following a rigorous process and spanning the breadth of detection approaches, using high-quality reference cell lines, as well as simulations. Due to the nature of available truth sets, our focus is on general-purpose rather than somatic callers. We characterise the impact on performance of event size and type, sequencing characteristics, and genomic context, and analyse the efficacy of ensemble calling and calibration of variant quality scores. Finally, we provide recommendations for both users and methods developers.

To examine global changes in breast heterogeneity across different states, we determined the single-cell transcriptomes of > 340,000 cells encompassing normal breast, preneoplastic BRCA1 +/tissue, the major breast cancer subtypes, and pairs of tumors and involved lymph nodes. Elucidation of the normal breast microenvironment revealed striking changes in the stroma of post-menopausal women. Single-cell profiling of 34 treatmentnaive primary tumors, including estrogen receptor (ER) + , HER2 + , and triple-negative breast cancers, revealed comparable diversity among cancer cells and a discrete subset of cycling cells. The transcriptomes of preneoplastic BRCA1 +/tissue versus tumors highlighted global changes in the immune microenvironment. Within the tumor immune landscape, proliferative CD8 + T cells characterized triple-negative and HER2 + cancers but not ER + tumors, while all subtypes comprised cycling tumor-associated macrophages, thus invoking potentially different immunotherapy targets. Copy number analysis of paired ER + tumors and lymph nodes indicated seeding by genetically distinct clones or mass migration of primary tumor cells into axillary lymph nodes. This large-scale integration of patient samples provides a highresolution map of cell diversity in normal and cancerous human breast.