See
Genome Information for Homo sapiens
We identified EGF as the top candidates predicting kidney function through an intrarenal transcriptome-driven approach, and demonstrated it is an independent risk predictor of CKD progression and can significantly improve prediction of renal outcome by established clinical parameters in diverse populations with CKD from a wide spectrum of causes and stages
Overall design: Chronic Kidney Disease, Lupus nephritis, Focal and Segmental Glomerulosclerosis, Nephropathies, Membranous Glomerulonephritis
| Accession | PRJNA285492; GEO: GSE69438 |
| Data Type | Transcriptome or Gene expression |
| Scope | Multiisolate |
| Organism | Homo sapiens[Taxonomy ID: 9606] Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Primates; Haplorrhini; Catarrhini; Hominidae; Homo; Homo sapiens |
| Publications | Ju W et al., "Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.", Sci Transl Med, 2015 Dec 2;7(316):316ra193 |
| Submission | Registration date: 1-Jun-2015
University of Michigan |
| Relevance | Medical |
Project Data:
| Resource Name | Number
of Links |
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| Publications |
| PubMed | 1 |
| PMC | 1 |
| Other datasets |
| GEO DataSets | 1 |
GEO Data Details| Parameter | Value |
|---|
| Data volume, Spots | 738612 |
| Data volume, Processed Mbytes | 13 |
| Data volume, Supplementary Mbytes | 187 |