title: CODEX: a normalization and copy number variation detection method for whole exome sequencing.
abstract: High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.
authors.affiliation: Genomics and Computational Biology Graduate Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
authors.forename: Yuchao
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Division of Oncology and Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
authors.forename: Derek A
authors.initials: DA
authors.lastname: Oldridge
authors.affiliation: Division of Oncology and Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
authors.forename: Sharon J
authors.initials: SJ
authors.lastname: Diskin
authors.affiliation: Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA nzh@wharton.upenn.edu.
authors.forename: Nancy R
authors.initials: NR
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001482:Base Composition; D015982:Bias; D016022:Case-Control Studies; D056915:DNA Copy Number Variations; D004265:DNA Helicases / Q000235:genetics; D004273:DNA, Neoplasm / Q000235:genetics; D030561:Databases, Nucleic Acid / Q000706:statistics & numerical data; D059472:Exome; D005260:Female; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D009447:Neuroblastoma / Q000235:genetics; D009687:Nuclear Proteins / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000706:statistics & numerical data; D000075924:X-linked Nuclear Protein
chemical_list: D004273:DNA, Neoplasm; D009687:Nuclear Proteins; D004265:DNA Helicases; C092332:ATRX protein, human; D000075924:X-linked Nuclear Protein