Systematic characterization of the composition and dynamics of processing body-associated mRNAs
RNA-seq (gene expression) · human · 597 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
- 597 samples: 41 conditions, mostly with about 11 replicates eachGroups 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
- Systematic characterization of the composition and dynamics of processing body-associated mRNAsNature communications · 2025
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 GSE279285_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 PRJNA1171800 and SRA study SRP537596. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 400 samples.
How we read this: 41 replicated groups read from the first 400 of 597 sample titles; they account for 400 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.
- GSM8563086 TRIBEID_1-SS3_1-SS3-A11 TRIBEID_1-SS3_1-SS3-A
- GSM8563087 TRIBEID_1-SS3_1-SS3-A12 TRIBEID_1-SS3_1-SS3-A
- GSM8563088 TRIBEID_1-SS3_1-SS3-A1 TRIBEID_1-SS3_1-SS3-A
- GSM8563089 TRIBEID_1-SS3_1-SS3-A2 TRIBEID_1-SS3_1-SS3-A
- GSM8563090 TRIBEID_1-SS3_1-SS3-A3 TRIBEID_1-SS3_1-SS3-A
- GSM8563091 TRIBEID_1-SS3_1-SS3-A4 TRIBEID_1-SS3_1-SS3-A
- GSM8563092 TRIBEID_1-SS3_1-SS3-A5 TRIBEID_1-SS3_1-SS3-A
- GSM8563093 TRIBEID_1-SS3_1-SS3-A6 TRIBEID_1-SS3_1-SS3-A
- GSM8563094 TRIBEID_1-SS3_1-SS3-A7 TRIBEID_1-SS3_1-SS3-A
- GSM8563095 TRIBEID_1-SS3_1-SS3-A9 TRIBEID_1-SS3_1-SS3-A
- GSM8563096 TRIBEID_1-SS3_1-SS3-B10 TRIBEID_1-SS3_1-SS3-B
- GSM8563097 TRIBEID_1-SS3_1-SS3-B11 TRIBEID_1-SS3_1-SS3-B
- GSM8563098 TRIBEID_1-SS3_1-SS3-B12 TRIBEID_1-SS3_1-SS3-B
- GSM8563099 TRIBEID_1-SS3_1-SS3-B4 TRIBEID_1-SS3_1-SS3-B
- GSM8563100 TRIBEID_1-SS3_1-SS3-B5 TRIBEID_1-SS3_1-SS3-B
- GSM8563101 TRIBEID_1-SS3_1-SS3-B6 TRIBEID_1-SS3_1-SS3-B
- GSM8563102 TRIBEID_1-SS3_1-SS3-B8 TRIBEID_1-SS3_1-SS3-B
- GSM8563103 TRIBEID_1-SS3_1-SS3-B9 TRIBEID_1-SS3_1-SS3-B
- GSM8563104 TRIBEID_1-SS3_1-SS3-C10 TRIBEID_1-SS3_1-SS3-C
- GSM8563105 TRIBEID_1-SS3_1-SS3-C11 TRIBEID_1-SS3_1-SS3-C
- GSM8563106 TRIBEID_1-SS3_1-SS3-C12 TRIBEID_1-SS3_1-SS3-C
- GSM8563107 TRIBEID_1-SS3_1-SS3-C1 TRIBEID_1-SS3_1-SS3-C
- GSM8563108 TRIBEID_1-SS3_1-SS3-C2 TRIBEID_1-SS3_1-SS3-C
- GSM8563109 TRIBEID_1-SS3_1-SS3-C3 TRIBEID_1-SS3_1-SS3-C
- GSM8563110 TRIBEID_1-SS3_1-SS3-C4 TRIBEID_1-SS3_1-SS3-C
- GSM8563111 TRIBEID_1-SS3_1-SS3-C5 TRIBEID_1-SS3_1-SS3-C
- GSM8563112 TRIBEID_1-SS3_1-SS3-C6 TRIBEID_1-SS3_1-SS3-C
- GSM8563113 TRIBEID_1-SS3_1-SS3-C7 TRIBEID_1-SS3_1-SS3-C
- GSM8563114 TRIBEID_1-SS3_1-SS3-C8 TRIBEID_1-SS3_1-SS3-C
- GSM8563115 TRIBEID_1-SS3_1-SS3-D10 TRIBEID_1-SS3_1-SS3-D
- GSM8563116 TRIBEID_1-SS3_1-SS3-D11 TRIBEID_1-SS3_1-SS3-D
- GSM8563117 TRIBEID_1-SS3_1-SS3-D12 TRIBEID_1-SS3_1-SS3-D
- GSM8563118 TRIBEID_1-SS3_1-SS3-D1 TRIBEID_1-SS3_1-SS3-D
- GSM8563119 TRIBEID_1-SS3_1-SS3-D2 TRIBEID_1-SS3_1-SS3-D
- GSM8563120 TRIBEID_1-SS3_1-SS3-D4 TRIBEID_1-SS3_1-SS3-D
- GSM8563121 TRIBEID_1-SS3_1-SS3-D5 TRIBEID_1-SS3_1-SS3-D
- GSM8563122 TRIBEID_1-SS3_1-SS3-D6 TRIBEID_1-SS3_1-SS3-D
- GSM8563123 TRIBEID_1-SS3_1-SS3-D7 TRIBEID_1-SS3_1-SS3-D
- GSM8563124 TRIBEID_1-SS3_1-SS3-D8 TRIBEID_1-SS3_1-SS3-D
- GSM8563125 TRIBEID_1-SS3_1-SS3-D9 TRIBEID_1-SS3_1-SS3-D
+ 557 more — browse all 597 samples with per-sample file links →
- GSE279284 Systematic characterization of the composition and dynamics of processing body-associated mRNAs [dataset 2] 131 samples shares body-associated, composition, systematic, processing, dynamics, mrnas
- GSE279168 Systematic characterization of the composition and dynamics of processing body-associated mRNAs [dataset 1] 458 samples shares body-associated, composition, systematic, processing, dynamics, mrnas
- GSE272219 Profiling transcriptome composition and dynamics within nuclear compartments using SLAM-RT&Tag 140 samples shares composition, dynamics
- GSE269274 Systematic analyses of transposable element expression dynamics using long read RNA-seq in pluripotent stem cells and germ lineage cells [subcellular RNA-seq] 46 samples shares systematic, dynamics
- GSE269273 Systematic analyses of transposable element expression dynamics using long read RNA-seq in pluripotent stem cells and germ lineage cells [bulk RNA-seq] 16 samples shares systematic, dynamics
- GSE274188 RAPIDASH: Tag-free enrichment of ribosome-associated proteins reveals compositional dynamics in embryonic tissues, cancer cells, and macrophages [RNA-Seq and Ribo-Seq] 12 samples shares composition, dynamics
- GSE313042 Systematic Bias Introduced by Ficoll-Based Isolation in AML Sample Composition and Downstream Analyses 10 samples shares composition, systematic
- GSE241685 Systematic identification and characterization of Exon-intron circRNAs in the human transcriptome 34 samples shares systematic
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.