Preanalytical Impacts on Copy Number Variation Detection by aCGH Technology
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PROVIDER: PRJNA477670 | ENA |
REPOSITORIES: ENA
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Project description:CNV plays an important role in the chicken genomic studies,it is imperative need to investigate the extent and pattern of CNVs using array comparative genomic hybridization (aCGH) in chinese chicken breeds for future studies associating phenotype to genome architecture. we describe systematic and genome-wide analysis of CNVs loci in five Chinese indigenous chicken breeds were evaluated by aCGH.
2014-10-10 | GSE49889 | GEO
Project description:BackgroundMale breast cancer (MBC) is a rare disease and little is known about its etiopathogenesis. Array comparative genomic hybridization (aCGH) provides a method to quantitatively measure the changes of DNA copy number and to map them directly onto the complete linear genome sequences. The aim of this study was to investigate DNA imbalances by aCGH and compare them with a female breast cancer dataset.MethodsWe used Agilent Human Genome CGH Microarray Kit 44B and 44K to compare genomic alterations in 25 male breast cancer tissues studied at NCC of Bari and 16 female breast cancer deposited with the Gene Expression Omnibus (GSE12659). Data analysis was performed with Nexus Copy Number 5.0 software.ResultsAll the 25 male and 16 female breast cancer samples displayed some chromosomal instability (110.93 alterations per patient in female, 69 in male). However, male samples presented a lower frequency of genetic alterations both in terms of loss and gains.ConclusionaCGH is an effective tool for analysis of cytogenetic aberrations in MBC, which involves different biological processes than female. Male most significant altered regions contained genes involved in cell communication, cell division and immunological response, while female cell-cell junction maintenance, regulation of transcription and neuron development.
| S-EPMC4605520 | biostudies-literature
Project description:CNV plays an important role in the chicken genomic studies,it is imperative need to investigate the extent and pattern of CNVs using array comparative genomic hybridization (aCGH) in chinese chicken breeds for future studies associating phenotype to genome architecture. we describe systematic and genome-wide analysis of CNVs loci in five Chinese indigenous chicken breeds were evaluated by aCGH. 5 Chinese native chicken were detected using ANKA broiler as reference.
2014-10-10 | E-GEOD-49889 | biostudies-arrayexpress
Project description:Genomic DNA copy-number alterations (CNAs) are associated with complex diseases, including cancer: CNAs are indeed related to tumoral grade, metastasis, and patient survival. CNAs discovered from array-based comparative genomic hybridization (aCGH) data have been instrumental in identifying disease-related genes and potential therapeutic targets. To be immediately useful in both clinical and basic research scenarios, aCGH data analysis requires accurate methods that do not impose unrealistic biological assumptions and that provide direct answers to the key question, "What is the probability that this gene/region has CNAs?" Current approaches fail, however, to meet these requirements. Here, we introduce reversible jump aCGH (RJaCGH), a new method for identifying CNAs from aCGH; we use a nonhomogeneous hidden Markov model fitted via reversible jump Markov chain Monte Carlo; and we incorporate model uncertainty through Bayesian model averaging. RJaCGH provides an estimate of the probability that a gene/region has CNAs while incorporating interprobe distance and the capability to analyze data on a chromosome or genome-wide basis. RJaCGH outperforms alternative methods, and the performance difference is even larger with noisy data and highly variable interprobe distance, both commonly found features in aCGH data. Furthermore, our probabilistic method allows us to identify minimal common regions of CNAs among samples and can be extended to incorporate expression data. In summary, we provide a rigorous statistical framework for locating genes and chromosomal regions with CNAs with potential applications to cancer and other complex human diseases.
| S-EPMC1894821 | biostudies-literature
Project description:aCGH Detects Copy Number Variation with Similar Resolution to PacBio Sequencing Approaches
| PRJNA595492 | ENA
Project description:Next-generation sequencing (NGS) technologies offer new opportunities for precise and accurate identification of genomic aberrations, including copy number variations (CNVs). For high-throughput NGS data, using depth of coverage has become a major approach to identify CNVs, especially for whole exome sequencing (WES) data. Due to the high level of noise and biases of read-count data and complexity of the WES data, existing CNV detection tools identify many false CNV segments. Besides, NGS generates a huge amount of data, requiring to use effective and efficient methods. In this work, we propose a novel segmentation algorithm based on the total variation approach to detect CNVs more precisely and efficiently using WES data. The proposed method also filters out outlier read-counts and identifies significant change points to reduce false positives. We used real and simulated data to evaluate the performance of the proposed method and compare its performance with those of other commonly used CNV detection methods. Using simulated and real data, we show that the proposed method outperforms the existing CNV detection methods in terms of accuracy and false discovery rate and has a faster runtime compared to the circular binary segmentation method.
| S-EPMC7278034 | biostudies-literature
Project description:Preanalytic Impacts on Genomic Sequencing by NGS technology
| PRJNA477669 | ENA
Project description:Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data.
| S-EPMC3245619 | biostudies-literature
Project description:We used Nimblegen HD aCGH to detect copy-number variants between genomes of BN and SHR rats
2010-01-30 | GSE20102 | GEO
Project description:We used Nimblegen HD aCGH to detect copy-number variants between genomes of BN and M520 rats
2012-12-31 | GSE27368 | GEO