10 research outputs found
Downregulation of Immunosuppressive Environment in Patients with Chronic HBV Hepatitis on Maintained Remission
Influence of Peroxide Impurities in Povidone on the Stability of Selected β-Blockers with the Help of HPLC
Novel expression of Neuropilin 1 on human tumor-infiltrating lymphocytes in colorectal cancer liver metastases
Hyperlipidemia Alters the Pharmacokinetics of Posaconazole and Vincristine Upon Co-Administration in Rats
Stability–Indicating Spectrofluorimetric Methods for the Determination of Metolazone and Xipamide in Their Tablets. Application to Content Uniformity Testing
A community effort to create standards for evaluating tumor subclonal reconstruction
Methods for reconstructing tumor evolution are benchmarked in the DREAM Somatic Mutation Calling Tumour Heterogeneity Challenge. Tumor DNA sequencing data can be interpreted by computational methods that analyze genomic heterogeneity to infer evolutionary dynamics. A growing number of studies have used these approaches to link cancer evolution with clinical progression and response to therapy. Although the inference of tumor phylogenies is rapidly becoming standard practice in cancer genome analyses, standards for evaluating them are lacking. To address this need, we systematically assess methods for reconstructing tumor subclonality. First, we elucidate the main algorithmic problems in subclonal reconstruction and develop quantitative metrics for evaluating them. Then we simulate realistic tumor genomes that harbor all known clonal and subclonal mutation types and processes. Finally, we benchmark 580 tumor reconstructions, varying tumor read depth, tumor type and somatic variant detection. Our analysis provides a baseline for the establishment of gold-standard methods to analyze tumor heterogeneity