Detection of a genomic duplication by copy number analysis
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ABSTRACT:
PROVIDER: PRJNA418983 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Comparative genomic hybridization of strains PN1 (no duplication) and PN1400 (duplication in Chromosome 3)
2018-05-31 | GSE107099 | GEO
Project description:Detection of genomic rearrangements from a single cell instead of a population of cells is an emerging research technique with important applications in the study of human fertility, constitutional chromosomal disorders, and tumor progression. Here, we develop a method to improve the detection of single-cell genome-wide copy number variation.
2011-08-24 | GSE27892 | GEO
Project description:Detection of genomic copy number variations induced by multiple DNA breaks
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Project description:Detailed analyses of the clone-based genome assembly reveal that the recent duplication content of mouse (4.94%) is now comparable to that of human (5.5%), in contrast to previous estimates from the whole-genome shotgun sequence assembly. The architecture of mouse and human genomes differ dramatically; most mouse duplications are organized into discrete clusters of tandem duplications that are depleted for genes/transcripts and enriched for LINE1 and LTR retroposons. We assessed copy-number variation of the C57BL/6J duplicated regions within 15 mouse strains used for genetic association studies, sequencing, and the mouse phenome project. We determined that over 60% of these basepairs are polymorphic between the strains (on average 20 Mbp of copy-number variable DNA between different mouse strains). Our data suggest that different mouse strains show comparable, if not greater, copy-number polymorphism when compared to human; however, such variation is more locally restricted. We show large and complex patterns of inter-strain copy-number variation restricted to large gene families associated with spermatogenesis, pregnancy, viviparity, phermone signaling, and immune response. Keywords: comparative genomic hybridization
2008-05-10 | GSE11369 | GEO
Project description:Copy Number Variations in Genomic Disorders
| PRJNA75521 | ENA
Project description:Detection of genomic rearrangements from a single cell instead of a population of cells is an emerging research technique with important applications in the study of human fertility, constitutional chromosomal disorders, and tumor progression. Here, we develop a method to improve the detection of single-cell genome-wide copy number variation. Additional information about the blastomeres can be found in GSE11663.
2011-08-10 | GSE31219 | GEO
Project description:Detailed analyses of the clone-based genome assembly reveal that the recent duplication content of mouse (4.94%) is now comparable to that of human (5.5%), in contrast to previous estimates from the whole-genome shotgun sequence assembly. The architecture of mouse and human genomes differ dramatically; most mouse duplications are organized into discrete clusters of tandem duplications that are depleted for genes/transcripts and enriched for LINE1 and LTR retroposons. We assessed copy-number variation of the C57BL/6J duplicated regions within 15 mouse strains used for genetic association studies, sequencing, and the mouse phenome project. We determined that over 60% of these basepairs are polymorphic between the strains (on average 20 Mbp of copy-number variable DNA between different mouse strains). Our data suggest that different mouse strains show comparable, if not greater, copy-number polymorphism when compared to human; however, such variation is more locally restricted. We show large and complex patterns of inter-strain copy-number variation restricted to large gene families associated with spermatogenesis, pregnancy, viviparity, phermone signaling, and immune response. Keywords: comparative genomic hybridization Genomic DNA of 14 inbred mouse strains was tested against reference C57BL/6J sample. C57BL/6J DNA sample from another individual was tested as negative control.
2008-05-10 | E-GEOD-11369 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60254 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60168 | GEO
Project description:Genomic copy number number characterisation of glioblastoma (GBM) cell lines.
| PRJNA489666 | ENA