ENVEENVE is a novel and robust methodology for detecting somatic copy-number alterations in massively parallel DNA sequencing data derived from stromal-admixed clinical samples. ENVE models inherent noise in whole-exome sequencing data using non-malignant tissue samples, and utilizes the learned model for robust estimation of sCNAs in tumors.
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InFloInFlo is a novel systems biology approach for characterizing the activities of complex signaling networks using a unique multidimensional framework integrating transcriptomic, genomic and/or epigenomic profiles for any given biological sample.
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