HDAC3 inhibition as a therapeutic strategy in T-cell acute lymphoblastic leukemia via the TYK2-STAT1-BCL2 signaling pathway
RNA-seq (gene expression) · human · 12 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
- Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
- Samples
- 12 samples: 6 × JC vs 6 × MCGroups 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 GSE316603_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 PRJNA1403461 and SRA study SRP662771. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 2 replicated groups read from 12 sample titles; they account for 12 of them. 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.
- GSM9456760 JC1 JC
- GSM9456761 JC3 JC
- GSM9456762 JC5 JC
- GSM9456763 JC2 JC
- GSM9456764 JC4 JC
- GSM9456765 JC6 JC
- GSM9456766 MC1 MC
- GSM9456767 MC3 MC
- GSM9456768 MC5 MC
- GSM9456769 MC2 MC
- GSM9456770 MC4 MC
- GSM9456771 MC6 MC
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- GSE12995 Expression data for diagnosis acute lymphoblastic leukemia samples 175 samples same disease briefing · shares lymphoblastic, leukemia
- GSE13425 Expression data from ALL patients included in the set used to construct a classification signature (COALL cohort) 190 samples same disease briefing
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- GSE18198 Expression profile of human T-ALL cell lines treated with DMSO or SAHM1 12 samples same disease briefing
- GSE272023 CpG island methylator phenotype classification improves risk assessment in pediatric T-cell Acute Lymphoblastic Leukemia [RNA-seq] 111 samples shares lymphoblastic, leukemia, t-cell
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.