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     Quick Explanation


    I can’t yet create *Platelet Gene Signatures from GSE293993* because the prompt provides no expression matrix, probe/ID mapping, or GSE293993 metadata/normalized countsβ€”only unrelated platelet biology studies. If you upload the GSE293993 matrix (or marker lists) or provide the processed expression table, I can generate platelet signatures and Plotly figures immediately (with rigorous citations to the uploaded/queried data provenance).


     Long Explanation


    Create Graphs: Platelet Gene Signatures from GSE293993
    Status: Blocked by missing raw data needed to compute signatures.
    What I’m missing (from your input)
    • GSE293993 expression data (e.g., normalized counts/TPM/log2, samples Γ— genes).
    • Normalization + preprocessing provenance (platform, whether RMA/DESeq2/limma-voom, log-transform, batch correction).
    • Gene identifiers (probe IDs vs gene symbols/Ensembl) plus probeβ†’gene mapping.
    • Labels needed to define β€œplatelet” vs β€œnon-platelet” (e.g., sorted cell type, plasma vs whole blood, stimulated vs control).
    Because no GSE293993 matrix/labels were provided here, I can’t truthfully compute gene signatures or reproduce any dataset-specific graphs.
    What I will generate once you provide GSE293993 data
    I’ll compute platelet gene signatures using an evidence-based workflow such as:
    • Platelet-enriched differential expression (cell-type contrast) with multiple testing correction.
    • Ranking of markers by effect size (logFC) and statistical support (adjusted p-values).
    • Signature robustness checks (stability across folds or sensitivity to threshold choices, if metadata allows).
    • Visualization:
      • Platelet marker volcano plot
      • Top-N heatmap
      • Signature score distributions (per sample)
      • Gene set enrichment-style summary (using ranked list)
    Fastest path
    Upload either:
    • a processed expression table (CSV/TSV): rows=genes, columns=samples (+ a sample label column), or
    • a raw GEO matrix plus platform annotation + sample phenotypes.
    Run the Science AI Agent to compute the signatures
    If you have already uploaded GSE293993 (or can upload it after this message), the agent will iteratively: (1) ingest the dataset, (2) compute platelet marker gene signatures, (3) produce Plotly figures (volcano/heatmap/signature score), (4) and return fully reproducible steps.


    Feedback:    

    Updated: March 19, 2026

     Top Data Sources ExportMCP


     Analysis Wizard



    Computes platelet-enriched markers from GSE293993 using expression + labels, applies multiple-testing correction, ranks genes, derives a signature score per sample, then renders volcano/heatmap plots.



     Potential Experiments


    N/A

     Science Art


    Create Graphs: Platelet Gene Signatures from GSE293993 Science Art

     Science Movie


    Make a narrated HD Science movie for this answer ($32 per minute)




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