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Identification of a Characteristic Copy Number Alteration Profile by High-Resolution single nucleotide polymorphism arrays Associated With Metastatic Sporadic Colorectal Cancer

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CANCER 2014年第13期120卷 1948-1959页

作者： Gonzalez-Gonzalez, Maria Fontanillo, Celia Abad, Maria M. Gutierrez, Maria L. Mota, Ines Bengoechea, Oscar Santos-Briz, Angel Blanco, Oscar Fonseca, Emilio Ciudad, Juana Fuentes, Manuel De Las Rivas, Javier Alcazar, Jose A. Garcia, Jacinto Munoz-Bellvis, Luis Orfao, Alberto Sayagues, Jose M. Univ Salamanca Gen Cytometry Serv Nucleus Dept Med E-37008 Salamanca Spain Univ Salamanca Canc Res Ctr Inst Mol Biol & Cellular Oncol E-37008 Salamanca Spain Univ Salamanca Salamanca Inst Biomed Res E-37008 Salamanca Spain Univ Salamanca Bioinformat & Funct Genom Unit Inst Mol Biol & Cellular Oncol Spanish Natl Res Council E-37008 Salamanca Spain CITRE Seville Spain Univ Hosp Salamanca Salamanca Inst Biomed Res Dept Pathol Salamanca Spain Univ Hosp Salamanca Salamanca Inst Biomed Res Med Oncol Serv Salamanca Spain Univ Hosp Salamanca Salamanca Inst Biomed Res Dept Gen & Digest Surg Salamanca Spain

BACKGROUND: Metastatic dissemination is the most frequent cause of death in patients with sporadic colorectal cancer (sCRC). It is believed that the metastatic process is related at least in part to a specific background of genetic alterations accumulated in cells from primary tumors, and the ability to detect such alterations is critical for the identification of patients with sCRC who are at risk of developing metastases. METHODS: The authors used high-resolution, 500-K single nucleotide polymorphism arrays to identify copy number alteration profiles present at diagnosis in primary tumors from patients with metastatic (n = 23) versus nonmetastatic (n = 26) sCRC. RESULTS: The results revealed a characteristic pattern of copy number alterations in metastatic sCRC tumors that involved losses of 23 regions at chromosomes 1p, 17p, and 18q, together with gains of 35 regions at chromosomes 7 and 13q. CONCLUSIONS: In line with expectations, the copy number profile investigated involved multiple genes that were associated previously with sCRC (ie, SMAD2) and/or the metastatic process (ie, podocalyxin-like [PODXL]), and it also was associated with a poorer outcome. (C) 2014 American Cancer Society.

关键词： liver metastases colorectal carcinoma copy number change single nucleotide polymorphism array

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High fidelity of whole-genome amplified DNA on high-density single nucleotide polymorphism arrays

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GENOMICS 2008年第6期92卷 452-456页

作者： Xing, Jinchuan Watkins, W. Scott Zhang, Yuhua Witherspoon, David J. Jorde, Lynn B. Univ Utah Dept Human Genet Eccles Inst Human Genet Salt Lake City UT 84112 USA

Current microarray technology allows researchers to genotype a large number of SNPs with relatively small amounts of DNA. Nevertheless, researchers and clinicians still frequently face the problem of acquiring enough high-quality DNA for analysis. Whole-genome amplification (WGA) methods offer a solution for this problem, and earlier studies have shown that WGA samples perform reasonably well in small-scale genetic analyses (e.g. Affymetrix 10K array). To determine the performance of WGA products on a large-scale genotyping array, we compared the Affymetrix 250K array genotyping results of genomic DNA and their WGA products from four individuals. Our results indicate that WGA product performs well on the 250K array compared to genomic DNA, especially when using the BRLMM calling algorithm. WGA samples have high call rates (97.5% on average, compared to 99.4% for genomic DNA) and excellent concordance rates with their corresponding genomic DNA samples (98.7% on average). In addition, no apparent systematic genomic amplification bias can be detected. This study demonstrates that, although there is a slight decrease in the total call rates, WGA methods provide a reliable approach for increasing the amount of DNA samples for use with a common SNP genotyping array. (C) 2008 Elsevier Inc. All rights reserved.

关键词： Whole-genome amplification WGA single nucleotide polymorphism array

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Ultrasound Phenotype, Genetic Analysis, and Pregnancy Outcomes of Fetuses With 1p36 Deletion Syndrome

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Molecular Genetics and Genomic Medicine 2025年第5期13卷

作者： Cai, Meiying Lin, Na Chen, Xuemei Huang, Hailong Guo, Nan Lin, Jiansong Xu, Liangpu Medical Genetic Diagnosis and Therapy Center Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics Fujian Medical University Fujian Key Laboratory for Prenatal Diagnosis and Birth Defect Fuzhou China Department of Pathology Fujian Maternal and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics Fujian Medical University Fuzhou China

Background: The intrauterine ultrasound phenotype, genotype, pregnancy outcome, and neonatal prognosis of fetuses with 1p36 deletion syndrome were retrospectively analyzed, as previous reports are limited. Methods: Pregnant women (25,000) who underwent interventional prenatal diagnosis between December 2016 and March 2024 were selected. Fetal villus tissue, amniotic fluid, or umbilical cord blood were extracted for single nucleotide polymorphism array (SNP-array) detection under ultrasound guidance. Results: Thirteen fetuses had 1p36 deletions involving fragments that were 0.46–22.5 Mb. Six and seven fetuses had large and small copy number variation (CNV) fragment deletions in the 1p36 region, respectively. Two fetuses had normal ultrasound phenotypes, three underwent early spontaneous abortion, one had isolated ventricular septal defect, one had isolated mild ventriculomegaly, two had mild ventriculomegaly associated with increased renal echogenicity, one had mild ventriculomegaly associated with ventricular septal defect, one had severe ventriculomegaly associated with ventricular septal defect and fetal growth restriction, one had tricuspid valve dysplasia, and one had nasal bone dysplasia. Three 1p36 deletions were de novo, and one was paternally inherited. There were three cases of early spontaneous abortion, seven terminations, and three routine postnatal follow-ups. Conclusions: High-resolution SNP-arrays are suitable for the prenatal diagnosis of 1p36 deletion syndrome. © 2025 The Author(s). Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC.

关键词： cardiac development prenatal single nucleotide polymorphism array ventriculomegaly

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Evaluation of 16 loci to examine the cross-species utility of single nucleotide polymorphism arrays

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ANIMAL GENETICS 2010年第2期41卷 199-202页

作者： Sechi, T. Coltman, D. W. Kijas, J. W. CSIRO Livestock Ind St Lucia Qld 4067 Australia DiRPA AGRIS Res Unit Sardinia Italy Univ Alberta Dept Biol Sci Edmonton AB T6G 2E9 Canada

P>Large collections of single nucleotide polymorphisms (SNPs) have recently been identified from a number of livestock genomes. This raises the possibility that SNP arrays might be useful for analysis in related species for which few genetic markers are currently available. To address the likely success of such an approach, the aim of this study was to examine the threshold number and position of flanking mutations which act to prevent genotype calls being produced. Sequence diversity was measured across 16 loci containing SNPs known either to work successfully between species or fail between species. In pairwise comparisons between domestic and wild sheep, sequence divergence surrounding working SNP assays was significantly lower than that surrounding non-functional assays. In addition, the location of flanking mismatches tended to be closer to the target SNP in loci that failed to generate genotype calls across species. The magnitude of sequence divergence observed for both working and non-functional assays was compared with the divergence separating domestic sheep from European Mouflon, African Barbary, goat and cattle. The results suggest that the utility of SNP arrays for analysis of shared polymorphism will be restricted to closely related pairs of species. Analysis across more divergent species will, however, be successful for other objectives, such as the identification of the ancestral state of SNPs.

关键词： sheep single nucleotide polymorphism single nucleotide polymorphism array

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Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays

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BMC BIOINFORMATICS 2011年第1期12卷 1-14页

作者： Hur, Youngmi Lee, Hyunju Gwangju Inst Sci & Technol Dept Informat & Commun Kwangju South Korea Johns Hopkins Univ Dept Appl Math & Stat Baltimore MD USA

Background: Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs. Results: In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12). Conclusions: Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets.

关键词： Wavelet Coefficient Cancer Related Gene single nucleotide polymorphism array Copy Number Aberration Circular Binary Segmentation

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Conditional random pattern model for copy number aberration detection

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BMC BIOINFORMATICS 2010年第1期11卷 1-16页

作者： Li, Fuhai Zhou, Xiaobo Huang, Wanting Chang, Chung-Che Wong, Stephen T. C. Methodist Hosp Res Inst Weill Cornell Med Coll Ctr Bioengn & InformatDept Radiol Houston TX 77030 USA Methodist Hosp Res Inst Weill Cornell Med Coll Dept Pathol Houston TX 77030 USA

Background: DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable. Results: This paper presents a conditional random pattern (CRP) model for CNA detection where much contextual cues are explored to suppress the noise and improve CNA detection accuracy. Both simulated and the real data are used to evaluate the proposed model, and the validation results show that the CRP model is more robust and reliable in the presence of noise for CNA detection using high density SNP array data, compared to a number of widely used software packages. Conclusions: The proposed conditional random pattern (CRP) model could effectively detect the CNA regions in the presence of noise.

关键词： single nucleotide polymorphism Marker single nucleotide polymorphism array single nucleotide polymorphism Locus Copy Number Aberration Copy Number Status

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Fast MCMC Sampling for Hidden Markov Models to Determine Copy Number Variations

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BMC BIOINFORMATICS 2011年第1期12卷 1-17页

作者： Mahmud, Md Pavel Schliep, Alexander Rutgers State Univ Dept Comp Sci Piscataway NJ 08854 USA Rutgers State Univ BioMaPS Inst Quantitat Biol Piscataway NJ 08854 USA

Background: Hidden Markov Models (HMM) are often used for analyzing Comparative Genomic Hybridization (CGH) data to identify chromosomal aberrations or copy number variations by segmenting observation sequences. For efficiency reasons the parameters of a HMM are often estimated with maximum likelihood and a segmentation is obtained with the Viterbi algorithm. This introduces considerable uncertainty in the segmentation, which can be avoided with Bayesian approaches integrating out parameters using Markov Chain Monte Carlo (MCMC) sampling. While the advantages of Bayesian approaches have been clearly demonstrated, the likelihood based approaches are still preferred in practice for their lower running times;datasets coming from high-density arrays and next generation sequencing amplify these problems. Results: We propose an approximate sampling technique, inspired by compression of discrete sequences in HMM computations and by kd-trees to leverage spatial relations between data points in typical data sets, to speed up the MCMC sampling. Conclusions: We test our approximate sampling method on simulated and biological arrayCGH datasets and high-density SNP arrays, and demonstrate a speed-up of 10 to 60 respectively 90 while achieving competitive results with the state-of-the art Bayesian approaches. Availability: An implementation of our method will be made available as part of the open source GHMM library from http://***.

关键词： Hide Markov Model Markov Chain Monte Carlo Copy Number Variation Expectation Maximization single nucleotide polymorphism array

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Spatial normalization improves the quality of genotype calling for Affymetrix SNP 6.0 arrays

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BMC BIOINFORMATICS 2010年第1期11卷 1-9页

作者： Chai, High Seng Therneau, Terry M. Bailey, Kent R. Kocher, Jean-Pierre A. Mayo Clin Div Biomed Stat & Informat Coll Med Rochester MN 55905 USA

Background: Microarray measurements are susceptible to a variety of experimental artifacts, some of which give rise to systematic biases that are spatially dependent in a unique way on each chip. It is likely that such artifacts affect many SNP arrays, but the normalization methods used in currently available genotyping algorithms make no attempt at spatial bias correction. Here, we propose an effective single-chip spatial bias removal procedure for Affymetrix 6.0 SNP arrays or platforms with similar design features. This procedure deals with both extreme and subtle biases and is intended to be applied before standard genotype calling algorithms. Results: Application of the spatial bias adjustments on HapMap samples resulted in higher genotype call rates with equal or even better accuracy for thousands of SNPs. Consequently the normalization procedure is expected to lead to more meaningful biological inferences and could be valuable for genome-wide SNP analysis. Conclusions: Spatial normalization can potentially rescue thousands of SNPs in a genetic study at the small cost of computational time. The approach is implemented in R and available from the authors upon request.

关键词： single nucleotide polymorphism Probe Pair single nucleotide polymorphism array Spatial Bias single nucleotide polymorphism Allele

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Comparison of methods to detect copy number alterations in cancer using simulated and real genotyping data

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BMC BIOINFORMATICS 2012年第1期13卷 1-12页

作者： Mosen-Ansorena, David Maria Aransay, Ana Rodriguez-Ezpeleta, Naiara CIC BioGUNE CIBERehd Derio 48160 Spain AZTI Tecnalia Marine Res Div Sukarrieta 48395 Spain

Background: The detection of genomic copy number alterations (CNA) in cancer based on SNP arrays requires methods that take into account tumour specific factors such as normal cell contamination and tumour heterogeneity. A number of tools have been recently developed but their performance needs yet to be thoroughly assessed. To this aim, a comprehensive model that integrates the factors of normal cell contamination and intra-tumour heterogeneity and that can be translated to synthetic data on which to perform benchmarks is indispensable. Results: We propose such model and implement it in an R package called CnaGen to synthetically generate a wide range of alterations under different normal cell contamination levels. Six recently published methods for CNA and loss of heterozygosity (LOH) detection on tumour samples were assessed on this synthetic data and on a dilution series of a breast cancer cell-line: ASCAT, GAP, GenoCNA, GPHMM, MixHMM and OncoSNP. We report the recall rates in terms of normal cell contamination levels and alteration characteristics: length, copy number and LOH state, as well as the false discovery rate distribution for each copy number under different normal cell contamination levels. Assessed methods are in general better at detecting alterations with low copy number and under a little normal cell contamination levels. All methods except GPHMM, which failed to recognize the alteration pattern in the cell-line samples, provided similar results for the synthetic and cell-line sample sets. MixHMM and GenoCNA are the poorliest performing methods, while GAP generally performed better. This supports the viability of approaches other than the common hidden Markov model (HMM)-based. Conclusions: We devised and implemented a comprehensive model to generate data that simulate tumoural samples genotyped using SNP arrays. The validity of the model is supported by the similarity of the results obtained with synthetic and real data. Based on these results an

关键词： Synthetic Data Recall Rate single nucleotide polymorphism array Allelic Ratio Baseline Shift

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SNP and gene networks construction and analysis from classification of copy number variations data

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BMC BIOINFORMATICS 2011年第Sup5期12卷 S4-S4页

作者： Liu, Yang Lee, Yiu Fai Ng, Michael K. Hong Kong Baptist Univ Dept Math Kowloon Tong Hong Kong Peoples R China

Background: Detection of genomic DNA copy number variations (CNVs) can provide a complete and more comprehensive view of human disease. It is interesting to identify and represent relevant CNVs from a genome-wide data due to high data volume and the complexity of interactions. Results: In this paper, we incorporate the DNA copy number variation data derived from SNP arrays into a computational shrunken model and formalize the detection of copy number variations as a case-control classification problem. More than 80% accuracy can be obtained using our classification model and by shrinkage, the number of relevant CNVs to disease can be determined. In order to understand relevant CNVs, we study their corresponding SNPs in the genome and a statistical software PLINK is employed to compute the pair-wise SNP-SNP interactions, and identify SNP networks based on their P-values. Our selected SNP networks are statistically significant compared with random SNP networks and play a role in the biological process. For the unique genes that those SNPs are located in, a gene-gene similarity value is computed using GOSemSim and gene pairs that have similarity values being greater than a threshold are selected to construct gene networks. A gene enrichment analysis show that our gene networks are functionally important. Experimental results demonstrate that our selected SNP and gene networks based on the selected CNVs contain some functional relationships directly or indirectly to disease study. Conclusions: Two datasets are given to demonstrate the effectiveness of the introduced method. Some statistical and biological analysis show that this shrunken classification model is effective in identifying CNVs from genome-wide data and our proposed framework has a potential to become a useful analysis tool for SNP data sets.

关键词： single nucleotide polymorphism Copy Number Variation single nucleotide polymorphism array Wellcome Trust Case Control Consortium single nucleotide polymorphism Position

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