Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia
收藏NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://www.omicsdi.org/dataset/ega/EGAS00001007078
下载链接
链接失效反馈官方服务:
资源简介:
In this study we generated single-cell whole transcriptome and surface marker expression data for 24 samples of 19 AML patients as well as one healthy donor. We followed the CITEseq protocol with the 3' 10x Genomics scRNAseq kit version 3.1 To increase the coverage of the mitochondrial genome we generated mitochondrial libraries following a protocol termed Optimized 10x. Based on TAPseq, we generated libraries to increase the coverage of selected nuclear SNVs. Exome sequencing was generated for 15 patients to identify nuclear variants. Bulk ATAC was obtained for 9 samples to facilitate the discovery of mitochondrial SNVs. MutaSeq (modified version of SmartsSeq2) was performed on cells from 3 patients. Targeted DNAseq from single-cell derived colonies was generated for 1 patient.EGA study EGAS00001007078
创建时间:
2023-04-03



