Ensemble learning for classifying single-cell data and projection across reference atlases
Single-cell data are being generated at an accelerating pace.How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types.
- Type: Other
- Archiver: European Genome-Phenome Archive (EGA)
Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data
Dataset ID | Description | Technology | Samples |
---|---|---|---|
EGAD00001006017 | Illumina NovaSeq 6000 | 1 | |
EGAD00001006018 | Illumina NovaSeq 6000 | 1 | |
EGAD00001006019 | Illumina NovaSeq 6000 | 1 | |
EGAD00001006020 | Illumina NovaSeq 6000 | 1 |