AML Profiling by scRNA-seq

scRNAseq data from AML and normal bone marrow

Description: Single-cell RNA sequencing and genotyping to profile 38,410 cells from 40 bone marrow aspirates, including 16 AML patients and five healthy donors. A machine learning classifier was applied to distinguish a spectrum of malignant cell types whose abundances varied between patients and between subclones in the same tumor.

Authors:

van Galen P, Hovestadt V, Wadsworth Ii MH, Hughes TK, Griffin GK, Battaglia S, Verga JA, Stephansky J, Pastika TJ, Lombardi Story J, Pinkus GS, Pozdnyakova O, Galinsky I, Stone RM, Graubert TA, Shalek AK, Aster JC, Lane AA & Bernstein BE

Lab: Minden

Release Date: 2019

Keywords: transcriptome single cell

Hosted on GEO

Citation

van Galen P, Hovestadt V, Wadsworth Ii MH, et al. Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity. Cell. 2019;176(6):1265‐1281.e24. doi:10.1016/j.cell.2019.01.031

DOI

83 Samples

Datatype:scRNA-seq

Species:Human

Disease Type:Acute Myeloid Leukemia (AML)

Contact

This dataset is available by request only.

Contact: Mark Minden

Contact email: Email