Blockade of PF4-induced Th1-Treg polarization enhances anti-tumor immunity (Bulk RNA-Seq)
RNA-seq (gene expression) · mouse · 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
- Mus musculus (mouse)
- Samples
- 12 samples: 3 × B16_mche_pos vs 3 × B16_mche_neg vs 3 × MC38_mche+ vs 3 × MC38_mcheGroups 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.
- Paper
- Platelet factor 4-induced T(H)1-T(reg) polarization suppresses antitumor immunityScience (New York, N.Y.) · 2024
Read the full summary ↓
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 GSE252052_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 PRJNA1057209 and SRA study SRP480134. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 4 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.
- GSM8502187 B16_mche_pos_12 B16_mche_pos
- GSM8502188 B16_mche_pos_11 B16_mche_pos
- GSM8502189 B16_mche_pos_3 B16_mche_pos
- GSM8502190 B16_mche_neg_12 B16_mche_neg
- GSM8502191 B16_mche_neg_11 B16_mche_neg
- GSM8502192 B16_mche_neg_3 B16_mche_neg
- GSM8502193 MC38_mche+_1 MC38_mche+
- GSM8502194 MC38_mche+_2 MC38_mche+
- GSM8502195 MC38_mche+_3 MC38_mche+
- GSM8502196 MC38_mche-_1 MC38_mche
- GSM8502197 MC38_mche-_2 MC38_mche
- GSM8502198 MC38_mche-_3 MC38_mche
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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.