Efficient and precise single-cell reference atlas mapping with Symphony
Efficient and precise single-cell reference atlas mapping with Symphony
AbstractRecent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony (https://github.com/immunogenomics/symphony), an algorithm for building large-scale, integrated reference atlases in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony in multiple real-world datasets, including (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells.
- BRIGHAM AND WOMEN'S HOSPITAL
- Harvard University United States
- HARVARD MEDICAL SCHOOL
- Brigham and Women's Faulkner Hospital United States
- Broad Institute United States
Genome, Science, Q, Computational Biology, Humans, Single-Cell Analysis, Article, Algorithms, Software
Genome, Science, Q, Computational Biology, Humans, Single-Cell Analysis, Article, Algorithms, Software
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