Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

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Dataset ID	Description	Technology	Samples
EGAD00001010187	Single-cell whole transcriptome and antibody expression for bone marrow samples from Cohorts A and B. CITEseq protocol was followed. 37 and 77 surface markers were measured in each cohort, respectively (see Supplementary Table 1). For details on cell sorting prior scRNAseq see the methods section of the manuscript.	Illumina NovaSeq 6000	49
EGAD00001010188	Bulk ATAC libraries were generated for patient samples A.1, A.3, A.5, A.6, A.7, A.11, A.12, A.13 and A.15. For each patient a library of CD3- cells (myeloid cells, considered tumor cells) and CD3+ cells (T cells, considered healthy) were generated.	Illumina NovaSeq 6000	18
EGAD00001010189	MutaSeq was applied to CD34+ cells from patient samples A.10, A.11 and A.12 of the study. The protocol followed is described in https://doi.org/10.1038/s41467-021-21650-1 and in the methods of the manuscript	NextSeq 500	3
EGAD00001010190	Libraries were constructed using SureSelect HS XT Target Enrichment System v6 (Agilent). For each patient a library of CD3- cells (myeloid cells, considered tumor cells) and CD3+ cells (T cells, considered healthy) were generated.	Illumina NovaSeq 6000	30
EGAD00001010191	Optimized 10x library to increase the coverage of the mitochondrial genome from 3’ 10x gene expression data. See details of the experimental method in the methods section of the manuscript	Illumina NovaSeq 6000	24
EGAD00001010192	Optimized 10x library to increase the coverage of selected nuclear variants from 3’ 10x Genomics scRNAseq data. SNVs were selected based on exome data and criteria described in the Supplementary Information of the manuscript.See details of the experimental method in the methods section of the manuscript	NextSeq 500	21
EGAD00001010193	Targeted DNA sequencing was applied to colonies grown from single-cells of patient A.6. The protocol followed is described in https://doi.org/10.1038/s41467-021-21650-1 and the methods of the manuscript	NextSeq 500	1

Publications	Citations
Identifying cancer cells from calling single-nucleotide variants in scRNA-seq data. Marot-Lassauzaie V, Beneyto-Calabuig S, Obermayer B, Velten L, Beule D, Haghverdi L. Bioinformatics 40: 2024 btae512	1