CODEX: a normalization and copy number variation detection method for whole exome sequencing

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 leve...

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Bibliographic Details
Published in:Nucleic acids research 2015-03, Vol.43 (6), p.e39-e39
Main Authors: Jiang, Yuchao, Oldridge, Derek A, Diskin, Sharon J, Zhang, Nancy R
Format: Article
Language:English
Subjects:
Algorithms
Base Composition
Bias
Case-Control Studies
Databases, Nucleic Acid - statistics & numerical data
DNA Copy Number Variations
DNA Helicases - genetics
DNA, Neoplasm - genetics
Exome
Female
High-Throughput Nucleotide Sequencing - methods
High-Throughput Nucleotide Sequencing - statistics & numerical data
Humans
Likelihood Functions
Male
Methods Online
Neuroblastoma - genetics
Nuclear Proteins - genetics
Sequence Analysis, DNA - methods
Sequence Analysis, DNA - statistics & numerical data
X-linked Nuclear Protein
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Summary: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.
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gku1363