10X single-cell RNA sequencing of bone marrow cells from MDS-RS patients and healthy donors
SND-ID: 2023-121-1. Version: 1. DOI: https://doi.org/10.48723/nq2a-1e03
Associated documentation
Citation
Creator/Principal investigator(s)
Pedro Luis Moura - Karolinska Institutet, Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)
Eva Hellström-Lindberg - Karolinska Institutet, Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)
Research principal
Karolinska Institutet - Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)
Description
This dataset consists of single-cell RNA sequencing data of bone marrow cells (CD34+ stem cells, GPA+ erythroblasts, ring sideroblasts and mononuclear cells) obtained from multiple healthy bone marrow donors and MDS-RS patients. The objective of this data collection was to assess several parameters on how the bone marrow of MDS-RS patients differs from that of healthy donors.
This dataset includes raw sequencing data in .fastq format, processed count matrices and associated pseudonymized metadata.
Processing: All samples were loaded onto Chromium Single Cell Chips (10x Genomics, CA, USA) at a target capture rate of 10,000 cells per sample. Single cell libraries were prepared using Chromium Next GEM Single Cell 3ʹ Kits v3.1 (10x Genomics) as per the manufacturer’s instructions, except 1µl additive ADT primers were added to the initial cDNA PCR amplification buffer and ADT libraries prepared as described in the Total-Seq B protocol (BioLegend) from the initial cDNA SPRI clean up. Libraries were pooled and sequenced on an Illumina NovaSeq 6000 (Illumina). Read pseudoalignment was performed aga
This dataset includes raw sequencing data in .fastq format, processed count matrices and associated pseudonymized metadata.
Processing: All samples were loaded onto Chromium Single Cell Chips (10x Genomics, CA, USA) at a target capture rate of 10,000 cells per sample. Single cell libraries were prepared using Chromium Next GEM Single Cell 3ʹ Kits v3.1 (10x Genomics) as per the manufacturer’s instructions, except 1µl additive ADT primers were added to the initial cDNA PCR amplification buffer and ADT libraries prepared as described in the Total-Seq B protocol (BioLegend) from the initial cDNA SPRI clean up. Libraries were pooled and sequenced on an Illumina NovaSeq 6000 (Illumina). Read pseudoalignment was performed against the GRCh38.p13 human genome assembly through kallisto v0.46.1 and bustools v0.40.0 was used for barcode and UMI counting.
The dataset consists of 2 folders:
- Processed_Count_Matrices
- Raw_FASTQ
And one xlsx file:
- Sample_key.xlsx
The folder Processed_Count_Matrices contains 1 rds file, 1 tsv file, 9 mtx files, and 18 txt files.
The folder Raw_FASTQ contains 27 GNU zipped fastq files, and 5 txt files.
The documentation file File_list_10x.txt contains a full list of the files in the dataset.
The total size of the dataset is approximately 21 GB. Show less..
Data contains personal data
Yes
Sensitive personal data
Yes
Type of personal data
Genetic and biological data of patients
Code key exists
Yes
Language
Unit of analysis
Population
Patients with Myelodysplastic neoplasms with ring sideroblasts (MDS-RS) and healthy donors
Study design
Preclinical study
Sampling procedure
Non-probability: Availability
Mixed probability and non-probability
Biobank is connected to the study
This study has used existing samples from a scientific collection or biobank
Scientific collection or biobank name: Karolinska Institutet MDS biobank
Type(s) of sample: Bone marrow cells
Responsible department/unit
Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)
Ethics Review
Stockholm - Ref. 2017/1090-31/4
Research area
Natural sciences (Standard för svensk indelning av forskningsämnen 2011)
Biological sciences (Standard för svensk indelning av forskningsämnen 2011)
Cell biology (Standard för svensk indelning av forskningsämnen 2011)
Genetics (Standard för svensk indelning av forskningsämnen 2011)
Bioinformatics and systems biology (Standard för svensk indelning av forskningsämnen 2011)
Hematology (Standard för svensk indelning av forskningsämnen 2011)
Keywords
Moura PL, Mortera Blanco T, Hofman IJ, Todisco G, Kretzschmar WW, Björklund AC, Creignou M, Hagemann-Jensen M, Ziegenhain C, Cabrerizo Granados D, Barbosa I, Walldin G, Jansson M, Ashley N, Mead AJ, Lundin V, Dimitriou M, Yoshizato T, Woll PS, Ogawa S, Sandberg R, Jacobsen SW, Hellström-Lindberg E. Erythroid differentiation enhances RNA mis-splicing in SF3B1-mutant myelodysplastic syndromes with ring sideroblasts. Cancer Res. 2023 Nov 3. doi: 10.1158/0008-5472.CAN-23-3038.
DOI:
https://doi.org/10.1158/0008-5472.CAN-23-3038
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