Structural variants (SV), usually defined as variation from kilobase to megabase including insertions, duplications, and inversions, presumably contribute to more base-pair differences between individuals than SNPs and have considerable effects on human phenotypic variation such as disease. Copy number variation (CNV), for example, is a type of structural variation exhibiting difference in copy number between two or more individuals. When fixed in population, it becomes what is known as Segmental Duplication (SD). Due to the biological significance and importance of SV implicated in recent findings, it has become one of the focuses in genetics lately. To this end, we have developed different experimental and computational approaches to detect and analyze SVs, particularly in the human genome.

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Recurrent repeat expansions in human cancer genomes
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Landscape and variation of novel retroduplications in 26 human populations.
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MetaSV: an accurate and integrative structural-variant caller for next generation sequencing.
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Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms.
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AlleleSeq: analysis of allele-specific expression and binding in a network framework.
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Identification of genomic indels and structural variations using split reads.
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Analysis of genomic variation in non-coding elements using population-scale sequencing data from the 1000 Genomes Project.
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CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing.
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Mapping copy number variation by population-scale genome sequencing.
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AGE: defining breakpoints of genomic structural variants at single-nucleotide resolution, through optimal alignments with gap excision.
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Segmental duplications in the human genome reveal details of pseudogene formation.
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Nucleotide-resolution analysis of structural variants using BreakSeq and a breakpoint library.
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PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data.
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MSB: a mean-shift-based approach for the analysis of structural variation in the genome.
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High-resolution copy-number variation map reflects human olfactory receptor diversity and evolution.
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Analysis of copy number variants and segmental duplications in the human genome: Evidence for a change in the process of formation in recent evolutionary history.
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The current excitement about copy-number variation: how it relates to gene duplications and protein families.
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Positive selection at the protein network periphery: evaluation in terms of structural constraints and cellular context.
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Paired-end mapping reveals extensive structural variation in the human genome.
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Systematic prediction and validation of breakpoints associated with copy-number variants in the human genome.
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Assessing the need for sequence-based normalization in tiling microarray experiments.
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Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool.
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High-resolution mapping of DNA copy alterations in human chromosome 22 using high-density tiling oligonucleotide arrays.
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Design optimization methods for genomic DNA tiling arrays.
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Fast optimal genome tiling with applications to microarray design and homology search.
P Berman, P Bertone, B Dasgupta, M Gerstein, MY Kao, M Snyder (2004). J Comput Biol 11: 766-85.


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