PKBFI3428ENDH

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    "accession": "PKBFI3428ENDH",
    "aliases": [
        "pankbase-consortium:140scRNAseqDonors_HPAP-IIDP-Prodo_v3.3_RUVnormalizedPseudoBulkCounts_DE_delta_DEresult"
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                "detail": "Released tabular file [PKBFI3428ENDH](/tabular-files/PKBFI3428ENDH/) has in progress subobject analysis step version [ce0270c1-3e40-4326-a24e-e142b7caa387](/analysis-step-versions/ce0270c1-3e40-4326-a24e-e142b7caa387/).",
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    "award": {
        "@id": "/awards/U24DK138512/",
        "component": "data coordination"
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    "content_type": "differential gene expression quantifications",
    "controlled_access": false,
    "creation_timestamp": "2025-06-17T18:31:20.539308+00:00",
    "derived_from": [
        "/matrix-files/PKBFI1553PGUM/"
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    "description": "Delta DE results with all genes with sufficient counts to go into the modeling process. 2.1. The prefiltering criteria is that we only keep protein-coding genes with >= 10 raw counts in >= 25% of samples. 2.2. There will be genes within the file that passed the criteria in 2.1 but has NA adj. p-value and non-NA values in other metrics.",
    "file_format": "txt",
    "file_set": "/analysis-sets/PKBDS5505XMWS/",
    "file_url": "https://pankbase-data-v1.s3.us-west-2.amazonaws.com/analysis_resources/single_cell_expression/20250522_data_for_platform/Delta_k-chosen_fdr0.05_all.txt",
    "gene_list_for": [],
    "href": "/tabular-files/PKBFI3428ENDH/@@download/PKBFI3428ENDH.txt.gz",
    "input_file_for": [],
    "integrated_in": [],
    "lab": {
        "@id": "/labs/pankbase-consortium/",
        "title": "Pankbase Consortium, PanKbase"
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    "loci_list_for": [],
    "md5sum": "1a726bf19cc09c8f389fbbec56df47a7",
    "release_timestamp": "2025-06-18T18:32:10.077144+00:00",
    "schema_version": "11",
    "status": "released",
    "submitted_by": {
        "@id": "/users/5e3038c4-baa5-4589-b3d8-ad2fe634e826/",
        "title": "Ying Sun"
    },
    "summary": "differential gene expression quantifications",
    "upload_status": "validated",
    "uuid": "2308605a-e5d0-4ccb-bcd7-f1ea8d8197e2"
}