ROTS: reproducible RNA-seq biomarker detector-prognostic markers for clear cell renal cell cancer
| Autor: | Krista Rantanen, Fatemeh Seyednasrollah, Panu Jaakkola, Laura L. Elo |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Datasets as Topic RNA-Seq Kaplan-Meier Estimate Biology Bioinformatics ta3111 03 medical and health sciences Renal cell carcinoma Biomarkers Tumor Genetics medicine Humans Carcinoma Renal Cell Gene Regulation of gene expression Internet Models Statistical Cell growth Computational Biology High-Throughput Nucleotide Sequencing Reproducibility of Results Prognosis medicine.disease ta3122 Kidney Neoplasms Gene Expression Regulation Neoplastic Clear cell renal cell carcinoma 030104 developmental biology ROC Curve Methods Online Biomarker (medicine) Algorithms Software Clear cell |
| Zdroj: | Nucleic Acids Research |
| ISSN: | 0305-1048 |
| Popis: | Recent comprehensive assessments of RNA-seq technology support its utility in quantifying gene expression in various samples. The next step of rigorously quantifying differences between sample groups, however, still lacks well-defined best practices. Although a number of advanced statistical methods have been developed, several studies demonstrate that their performance depends strongly on the data under analysis, which compromises practical utility in real biomedical studies. As a solution, we propose to use a data-adaptive procedure that selects an optimal statistic capable of maximizing reproducibility of detections. After demonstrating its improved sensitivity and specificity in a controlled spike-in study, the utility of the procedure is confirmed in a real biomedical study by identifying prognostic markers for clear cell renal cell carcinoma (ccRCC). In addition to identifying several genes previously associated with ccRCC prognosis, several potential new biomarkers among genes regulating cell growth, metabolism and solute transport were detected. |
| Databáze: | OpenAIRE |
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