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)

4 Datasets

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	Single Cell RNA-Seq of Primary GBM. Gender Female, Age, 57.	Illumina NovaSeq 6000	1
EGAD00001006018	Mixed Sample of scRNA-Seq primary low grade glioma. Genders: Male, Age: 34, 44.	Illumina NovaSeq 6000	1
EGAD00001006019	Single Cell-RNA Seq of Wildtype Primary GBM for Female, Age 50.	Illumina NovaSeq 6000	1
EGAD00001006020	Primary diffuse astrocytoma G3 Male, 74	Illumina NovaSeq 6000	1