RNA-seq in acute myeloid leukemia (AML) cells with and without knockdown of METTL14
RNA-seq (gene expression) · human · 8 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)
- Samples
- 8 samples
- 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 GSE97443_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 PRJNA381786 and SRA study SRP103115. Searching any of these in the dataset finder brings you back here.
The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.
+ 8 more — browse all 8 samples with per-sample file links →
- GSE260773 RNA-seq Analysis of Acute myeloid leukemia (AML) primary samples 69 samples shares aml, leukemia, rna-seq, myeloid, acute
- GSE289786 Improved Prediction of Venetoclax and Azacitidine Efficacy in Acute Myeloid Leukemia through Machine Learning [AML patients] 142 samples shares aml, leukemia, myeloid, acute
- GSE229736 Therapy Induced Senescence Promotes Immunogenicity in Acute Myeloid Leukemia through Reduced EZH2 Activity (RNA-seq AraC) 12 samples shares leukemia, rna-seq, myeloid, acute
- GSE250160 IRF2BP2-mediated MHC-I expression controls cytotoxic T cell responses in acute myeloid leukemia [RNA-Seq] 12 samples shares leukemia, rna-seq, myeloid, acute
- GSE272023 CpG island methylator phenotype classification improves risk assessment in pediatric T-cell Acute Lymphoblastic Leukemia [RNA-seq] 111 samples shares leukemia, rna-seq, acute
- GSE272681 The cellular hierarchy of acute myeloid leukemia informs personalized treatment 108 samples shares leukemia, myeloid, acute
- GSE281506 Combining Menin and MEK inhibition to target poor prognosis KMT2A-rearranged RAS pathway-mutant acute myeloid leukemia 42 samples shares leukemia, myeloid, acute
- GSE269669 Phase Ib/II Study of Azacitidine, Venetoclax and Magrolimab in Adult Patients with Newly Diagnosed and Relapsed Refractory Acute Myeloid Leukemia 27 samples shares leukemia, myeloid, acute
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.