Uncovering the Dynamics of Immune Cell Populations in the First Week of Life: The Interplay of Neutrophils and Breastfeeding
RNA-seq (gene expression) · human · 178 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
- 178 samples: 178 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.
- Paper
- Population-specific heterogeneity in ontogeny of the broadly-conserved blood transcriptional program during the first week of lifeNature communications · 2026
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 GSE275823_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 PRJNA1153034 and SRA study SRP529014. 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 178 sample titles: 178 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.
- GSM8485949 G737H_1D87_Ontogency
- GSM8485950 G759K_1D89_Ontogency
- GSM8485951 G726A_1F08_Ontogency
- GSM8485952 P033_1F51_Ontogency
- GSM8485953 G750E_1M07_Ontogency
- GSM8485954 P037_1P35_Ontogency
- GSM8485955 P018_1T23_Ontogency
- GSM8485956 P035_1T97_Ontogency
- GSM8485957 G761D_1U56_Ontogency
- GSM8485958 G762B_1U79_Ontogency
- GSM8485959 P044_2A10_Ontogency
- GSM8485960 G736G_2G73_Ontogency
- GSM8485961 G748B_2J51_Ontogency
- GSM8485962 G722G_2L45_Ontogency
- GSM8485963 P039_2M12_Ontogency
- GSM8485964 G735D_2P55_Ontogency
- GSM8485965 G724H_2S11_Ontogency
- GSM8485966 P012_2U19_Ontogency
- GSM8485967 P026_2U83_Ontogency
- GSM8485968 P038_3B01_Ontogency
- GSM8485969 G743F_3B31_Ontogency
- GSM8485970 G738K_3D80_Ontogency
- GSM8485971 G763H_3F05_Ontogency
- GSM8485972 G730C_3F20_Ontogency
- GSM8485973 P029_3F41_Ontogency
- GSM8485974 P014_3G56_Ontogency
- GSM8485975 P016_3L70_Ontogency
- GSM8485976 P022_3Q99_Ontogency
- GSM8485977 P019_3S38_Ontogency
- GSM8485978 P043_3S86_Ontogency
- GSM8485979 G732J_4A74_Ontogency
- GSM8485980 P030_4B83_Ontogency
- GSM8485981 P045_4G54_Ontogency
- GSM8485982 G721J_4K65_Ontogency
- GSM8485983 G723K_4L48_Ontogency
- GSM8485984 G749H_4M44_Ontogency
- GSM8485985 P024_4Q69_Ontogency
- GSM8485986 P008_4R46_Ontogency
- GSM8485987 P040_5B97_Ontogency
- GSM8485988 G744D_5B98_Ontogency
+ 138 more — browse all 178 samples with per-sample file links →
- GSE261334 Dynamics and single-cell transcriptomics of circulating immune cell populations in inflammatory bowel disease upon anti-integrin treatment 29 samples shares populations, dynamics
- GSE301390 Prediction and Characterization of Genetically-Regulated Expression of Asthma Tissues from African-Ancestry Populations 260 samples shares populations
- GSE334369 Paradoxical Phenotype of Fibromyalgia Neutrophils: Elevated Baseline Inflammation but Blunted Response to Stimulation 206 samples shares neutrophils
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares populations
- GSE310957 DeCAF redefines fibroblast states uncovering multidimensional tumor-stroma relationships driving clinical tumor progression and immunotherapy response [RNA-Seq] 129 samples shares uncovering
- GSE324265 Contribution of cytotoxic CD8 T cells, neutrophils and type 1 interferon signaling to hyperinflammatory pathology in HIV associated TB meningitis [RNA-Seq] 125 samples shares neutrophils
- GSE233478 RNA-seq profiling of human hematopoietic cell populations across development. 106 samples shares populations
- GSE278206 Characterization of the transcriptional profile of circulating neutrophils from COPD patients [RNA-Seq] 77 samples shares neutrophils
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.