PSSV: a novel pattern-based probabilistic approach for somatic structural variation identification

Abstract

Motivation: Whole genome DNA-sequencing (WGS) of paired tumor and normal samples has enabled the identification of somatic DNA changes in an unprecedented detail. Large-scale identification of somatic structural variations (SVs) for a specific cancer type will deepen our understanding of driver mechanisms in cancer progression. However, the limited number of WGS samples, insufficient read coverage, and the impurity of tumor samples that contain normal and neoplastic cells, limit reliable and accurate detection of somatic SVs.Results: We present a novel pattern-based probabilistic approach, PSSV, to identify somatic structural variations from WGS data. PSSV features a mixture model with hidden states representing different mutation patterns; PSSV can thus differentiate heterozygous and homozygous SVs in each sample, enabling the identification of those somatic SVs with heterozygous mutations in normal samples and homozygous mutations in tumor samples. Simulation studies demonstrate that PSSV outperforms existing tools. PSSV has been successfully applied to breast cancer data to identify somatic SVs of key factors associated with breast cancer development. Availability and Implementation: An R package of PSSV is available at

GIP: A Gene network-based integrative approach for Inferring disease-associated signaling Pathways

“…The sampling framework has the felxibility to incorporate other genomic signals or other types of gene interactions to identify dysregulated signaling pathways. For example, many breast cancer genes carry somatic mutations 23,24 . Such information can be integrated with mRNA expression to refine our pathway identification.…”

MSIGNET: a Metropolis sampling-based method for global optimal significant network identification

“…They are closely related to Parkinson's disease and usually happen to people over 60 years old. Through functional annotation, the 159 genes also evolve in neurological system regulation (20), leaning, memory and behavior (10), cell cycle (14) and cell death or apoptosis (20). All these functions are closely related to the development of Parkinson's disease.…”

“…TCGA database, at the gene expression level, it becomes feasible to study the difference between normal samples and disease samples. Moreover, for drug resistance or cancer recurrence, besides genomic analysis focusing on somatic mutations (10,11), rewiring of gene interactions in recurrent vs. non-recurrent may guide us to identify recurrence related signalling pathways. And network based prediction has been demonstrated to be more power than gene based classification (12).…”

Multicenter validation of cancer gene panel-based next-generation sequencing for translational research and molecular diagnostics

“…Whole genome sequencing (WGS) or whole exome sequencing (WES) are excellent tools for the comprehensive and explorative detection of genetic alterations in tumor DNA extracted from cancer cells and tissues [ 10 ]. However, these techniques produce overwhelming amounts of data that require extensive bioinformatics analyses [ 5 ]. Moreover, for proper interpretation of disease-associated somatic variations in the tumor DNA, sequencing of constitutive germline specimen from the same patient is essential [ 8 ].…”