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license: mit

Data Card: Hyperinflammatory/Hypoinflammatory Sepsis Phenotype Whole-Blood RNA-seq Dataset (GSE236892)

Summary

Expression + sample metadata + feature metadata for GSE236892, a whole-blood RNA-seq study comparing the hyperinflammatory and hypoinflammatory molecular phenotypes of sepsis — two phenotypes previously identified by latent class analysis (LCA) across multiple cohorts, with divergent clinical outcomes and treatment responses. The study reports 5,755 differentially expressed genes (31% of genes tested) between phenotypes: hyperinflammatory patients showed elevated innate immune response gene expression, hypoinflammatory patients showed elevated adaptive/T-cell response gene expression. The study also reports concordance with other previously described sepsis/ARDS molecular subtypes (SRS1-2, MARS1-4, reactive/uninflamed) and a plasma metagenomic analysis (not part of this GEO deposit).

Source accession

Accession N (patients) Retrieval source
GSE236892 113 hypoinflammatory + 76 hyperinflammatory = 189 NCBI GEO

Files

  • sample_metadata.parquet — one row per sample: sample_id, age (integer; see note on imputed_age), sex, lca_label (factor, Hypo/Hyper — the LCA-assigned phenotype), imputed_age (logical), age_scaled (numeric, standardized)
  • feature_metadata.parquet — one row per gene (feature_id, Ensembl gene ID, version suffix stripped): gene coordinates from a GENCODE v49 GTF-derived TxDb, gene symbol/name/type from org.Hs.eg.db, plus two derived flags: autosomal_protein_coding and hemoglobin_related (see notes)
  • expression.parquet — single file, long format: feature_id, sample_id, value

Sample metadata field notes

  • lca_label is the phenotype variable used in this dataset — patients were previously assigned Hyper/Hypo status via latent class analysis in the source study, not derived here. A separate sepsis_group value was parsed from the sample title field during retrieval but was not carried into the final stored metadata; lca_label is the field to use.
  • age: some source values were recorded as "90+" rather than a specific integer. These were coerced to 90 and flagged via imputed_age = TRUE — treat age as a floor, not an exact value, for any sample where imputed_age is TRUE.
  • age_scaled is age standardized (mean-centered, unit variance) — provided for direct use as a model covariate; not a raw clinical value.

Feature metadata notes

  • Gene coordinates/annotation come from GENCODE v49. Genes present in the count matrix but absent from the GENCODE v49 TxDb: There are 378 that did not map btwn the cnt matrix and the v49 annotations. those are assigned to chrUn in the feature_meta.
  • autosomal_protein_coding flags genes that are protein-coding (per GENETYPE) and on an autosome (chr1–22) — useful as a standard filtering criterion for downstream analyses, computed here rather than left for every user to redefine themselves.
  • hemoglobin_related flags the 12 major hemoglobin genes/pseudogenes (HBA1, HBA2, HBB, HBBP1, HBD, HBE1, HBG1, HBG2, HBM, HBQ1, HBZ, HBZP1) — relevant for whole-blood RNA-seq, where globin transcript abundance is a common QC/filtering consideration.

Expression value processing

Raw, integer gene-level counts, as provided in the submitter's supplementary count matrix. No normalization or filtering applied here.

Provenance / reproducibility

See pull_gse236892.R