Expression Analysis (RNA-Seq) of adult Myelodysplastic Syndromes (MDS)/Acute Myeloid Leukemia (AML) with isolated monosomy 7 compared to controls
RNA-seq (gene expression) · human · 45 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Topic
- Myelodysplastic syndromesThis series is part of our curated briefing on it.
- Samples
- 45 samples: 45 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE211032_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA868719 and SRA study SRP391070. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 45 sample titles: 45 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM6447676 Mon7_1_RNAseq
- GSM6447677 Mon7_2_RNAseq
- GSM6447678 Mon7_3_RNAseq
- GSM6447679 CTL_1_RNAseq
- GSM6447680 CTL_2_RNAseq
- GSM6447681 CTL_3_RNAseq
- GSM6447682 dicMN_1_RNAseq
- GSM6447683 dicMN_2_RNAseq
- GSM6447684 dicMN_3_RNAseq
- GSM6447685 dicMN_4_RNAseq
- GSM6447686 dicMN_5_RNAseq
- GSM9267794 Mon7_4_RNAseq
- GSM9267795 Mon7_5_RNAseq
- GSM9267796 Mon7_6_RNAseq
- GSM9267797 Mon7_7_RNAseq
- GSM9267798 Mon7_8_RNAseq
- GSM9267799 Mon7_9_RNAseq
- GSM9267800 Mon7_10_RNAseq
- GSM9267801 Mon7_11_RNAseq
- GSM9267802 Mon7_12_RNAseq
- GSM9267803 Mon7_13_RNAseq
- GSM9267804 Mon7_14_RNAseq
- GSM9267805 Mon7_15_RNAseq
- GSM9267806 Mon7_16_RNAseq
- GSM9267807 Mon7_17_RNAseq
- GSM9267808 Mon7_18_RNAseq
- GSM9267809 nkMN_1_RNAseq
- GSM9267810 nkMN_2_RNAseq
- GSM9267811 nkMN_3_RNAseq
- GSM9267812 nkMN_4_RNAseq
- GSM9267813 nkMN_5_RNAseq
- GSM9267814 nkMN_6_RNAseq
- GSM9267815 nkMN_7_RNAseq
- GSM9267816 nkMN_8_RNAseq
- GSM9267817 nkMN_10_RNAseq
- GSM9267818 CTL_4_RNAseq
- GSM9267819 CTL_5_RNAseq
- GSM9267820 CTL_6_RNAseq
- GSM9267821 CTL_7_RNAseq
- GSM9267822 CTL_8_RNAseq
+ 5 more — browse all 45 samples with per-sample file links →
- GSE270760 PRC2-mediated apoptosis evasion is a therapeutic target of MDS/AML harboring inv(3)/t(3;3) and monosomy 7 (CUT&Tag) 24 samples same disease briefing · shares mds, aml, monosomy
- GSE31174 Affymetrix SNP array data for myelodysplastic syndromes (MDS) and related neoplasms 58 samples same disease briefing · shares mds, myelodysplastic, syndromes
- GSE288862 ScRNA-Seq of Human MDS and AML Bone Marrow Marrow Microenvironment. 3 samples same disease briefing · shares mds, aml
- GSE261339 Genome-Wide CRISPR-Cas9 Screening Identifies a Synergy between Hypomethylating Agents and SUMOylation Blockade in Myelodysplastic Syndromes and Acute Myeloid Leukemia 18 samples same disease briefing · shares myelodysplastic, syndromes, leukemia
- GSE284647 The genotype-integrated gene expression profile at the single-cell level of bone marrow CD34-positive hematopoietic stem and progenitor cells (HSPCs) from a patient with myelodysplastic neoplasms (MDS) harboring germline and somatic DDX41 variants. 1 samples same disease briefing · shares mds, myelodysplastic
- GSE292039 Splicing of erythroid transcription factor is associated with therapeutic response in myelodysplastic syndromes 27 samples same disease briefing · shares myelodysplastic, syndromes
- GSE237148 Targeting IL-1b–mediated inflammatory signaling overcomes transfusion dependence in early-stage myelodysplastic syndromes 26 samples same disease briefing · shares myelodysplastic, syndromes
- GSE290183 Distinct routes of clonal progression in SF3B1-mutant myelodysplastic syndromes 15 samples same disease briefing · shares myelodysplastic, syndromes
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.