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Normalized, Segmented or Called aCGH Data?
Wessel N. van Wieringen,Mark A. van de Wiel,Bauke Ylstra
Cancer Informatics , 2007,
Abstract: Array comparative genomic hybridization (aCGH) is a high-throughput lab technique to measure genome-wide chromosomal copy numbers. Data from aCGH experiments require extensive pre-processing, which consists of three steps: normalization, segmentation and calling. Each of these pre-processing steps yields a different data set: normalized data, segmented data, and called data. Publications using aCGH base their fi ndings on data from all stages of the pre-processing. Hence, there is no consensus on which should be used for further down-stream analysis. This consensus is however important for correct reporting of findings, and comparison of results from different studies. We discuss several issues that should be taken into account when deciding on which data are to be used. We express the believe that called data are best used, but would welcome opposing views.
Molecular cytogenetic characterisation of a mosaic add(12)(p13.3) with an inv dup(3)(q26.31 → qter) detected in an autistic boy
Isabel M Carreira, Joana B Melo, Carlos Rodrigues, Liesbeth Backx, Joris Vermeesch, Anja Weise, Nadezda Kosyakova, Guiomar Oliveira, Eunice Matoso
Molecular Cytogenetics , 2009, DOI: 10.1186/1755-8166-2-16
Abstract: We present the results of the molecular cytogenetic characterization of an unbalanced mosaic karyotype consisting of mos 46,XY,add(12)(p13.3) [56]/46,XY [44] in a previously described 11 years old autistic boy, re-evaluated at adult age. The employment of fluorescence in situ hybridization (FISH) and multicolor banding (MCB) techniques identified the extra material on 12p to be derived from chromosome 3, defining the additional material on 12p as an inv dup(3)(qter → q26.3::q26.3 → qter). Subsequently, array-based comparative genomic hybridization (aCGH) confirmed the breakpoint at 3q26.31, defining the extra material with a length of 24.92 Mb to be between 174.37 and 199.29 Mb.This is the thirteenth reported case of inversion-duplication 3q, being the first one described as an inv dup translocated onto a non-homologous chromosome. The mosaic terminal inv dup(3q) observed could be the result of two proposed alternative mechanisms. The most striking feature of this case is the autistic behavior of the proband, a characteristic not shared by any other patient with tetrasomy for 3q26.31 → 3qter. The present work further illustrates the advantages of the use of an integrative cytogenetic strategy, composed both by conventional and molecular techniques, on providing powerful information for an accurate diagnosis. This report also highlights a chromosome region potentially involved in autistic disorders.According to the orientation of the duplicated segment, duplications may be classified either as tandem or inverted, being the last usually associated with deletion of the distal region of the duplicated chromosome [1]. The best studied cases of inverted duplications (inv dup) are the inv dup(8p) [2,3] and bisatellited inv dup(15) [4], which are usually non-mosaic. In contrast, mosaic inverted duplications are derived from different post-zygotic mechanisms for which various possible origins have been proposed [5-7]. There is also a particular subset of inv dup in which the
aCGHViewer: A Generic Visualization Tool For aCGH data
Ganesh Shankar,Michael R. Rossi,Devin E. McQuaid,Jeffrey M. Conroy
Cancer Informatics , 2006,
Abstract: Array-Comparative Genomic Hybridization (aCGH) is a powerful high throughput technology for detecting chromosomal copy number aberrations (CNAs) in cancer, aiming at identifying related critical genes from the affected genomic regions. However, advancing from a dataset with thousands of tabular lines to a few candidate genes can be an onerous and time-consuming process. To expedite the aCGH data analysis process, we have developed a user-friendly aCGH data viewer (aCGHViewer) as a conduit between the aCGH data tables and a genome browser. The data from a given aCGH analysis are displayed in a genomic view comprised of individual chromosome panels which can be rapidly scanned for interesting features. A chromosome panel containing a feature of interest can be selected to launch a detail window for that single chromosome. Selecting a data point of interest in the detail window launches a query to the UCSC or NCBI genome browser to allow the user to explore the gene content in the chromosomal region. Additionally, aCGHViewer can display aCGH and expression array data concurrently to visually correlate the two. aCGHViewer is a stand alone Java visualization application that should be used in conjunction with separate statistical programs. It operates on all major computer platforms and is freely available at http://falcon.roswellpark.org/aCGHview/.
Detection of divergent genes in microbial aCGH experiments
Lars Snipen, Dirk Repsilber, Ludvig Nyquist, Andreas Ziegler, ?got Aakra, Are Aastveit
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-181
Abstract: We introduce a more efficient method for analyzing microbial aCGH data using a finite mixture model and a data rotation scheme. Using the average posterior probabilities from the model fitted to log-ratios before and after rotation, we get a score for each gene, and demonstrate its advantages for ranking and detecting divergent genes with enlarged specificity and sensitivity.The procedure is tested and compared to other approaches on simulated data sets, as well as on four experimental validation data sets for aCGH analysis on fully sequenced strains of Staphylococcus aureus and Streptococcus pneumoniae.When tested on simulated data as well as on four different experimental validation data sets from experiments with only fully sequenced strains, our procedure out-competes the standard procedures of using a simple log-ratio cutoff for classification into present and divergent genes.The genetic diversity among bacteria mirrors their lifestyles and physiological versatilities and evolves from adaptation to their niches and growth conditions. Many techniques have been used to obtain a picture of true microbial diversity. Microarray-based comparative genome hybridization (aCGH) is now a commonly used tool in comparative genomics. Compared to sequencing and comparing whole genomes, aCGH provides rapid genomotyping in bacteria [1,2].The majority of applications of aCGH is in cancer-research, where copy-number abberations is the primary focus [3,4]. Several methods have been suggested to analyze such data, e.g. [5-7].In microbial studies of genome diversity, usually one fully sequenced strain, called index strain, is compared to a set of unsequenced strains of the same or closely related bacterial species, called sample strains. In this setting it is of interest to characterize the sample strains with respect to the genes they have in common with the index strain, and those which are absent or highly divergent.In theory, every given gene is either present or divergent in th
SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets
Carmen Lai, Hugo M Horlings, Marc J van de Vijver, Eric H van Beers, Petra M Nederlof, Lodewyk FA Wessels, Marcel JT Reinders
BMC Bioinformatics , 2007, DOI: 10.1186/1471-2105-8-422
Abstract: We propose a supervised algorithm for the analysis of aCGH data and the identification of regions of chromosomal alteration (SIRAC). We first determine the DNA-probes that are important to distinguish the classes of interest, and then evaluate in a systematic and robust scheme if these relevant DNA-probes are closely located, i.e. form a region of amplification/deletion. SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.We illustrate the features of the algorithm with the use of a simple artificial dataset. The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.Genomic alterations in DNA copy number are important events in cancer development [1]. A tumor suppressor gene can be disabled by the physical loss of the gene, or similarly an oncogene may be over-expressed via the amplification of the region where it is located. The identification of chromosomal aberrations is, therefore, a powerful instrument in studies of cancer. It may suggest target genes for new drugs or shed light on the mechanisms which regulate the response to therapies [2-4].The first approach to search for copy number alterations in CGH has been made by Kallioniemi et al. [5] using metaphase chromosomes. The extensions of this technique employ array technology to perform a high resolution scan of the genome. As reviewed by Pinkel et al. [3], several array CGH (aCGH) techniques have been developed. The spotting technology makes use of BAC clones (100 – 200 kb), cDNA clones (~100 – 1000 bp) and lately oligonucleotides (30 – 100 bp). More recently, in-situ technologies synthesize small oligonucleotides directly onto the array. Since the oligos can be a few tens bp long, higher resolution are reached, if a good coverage of the genome is adopted.An important challenge to analyze aCGH data is to find the aberrated ch
A Fast and Flexible Method for the Segmentation of aCGH Data  [PDF]
Erez Ben-Yaacov,Yonina Eldar
Quantitative Biology , 2008,
Abstract: Motivation: Array Comparative Genomic Hybridization (aCGH) is used to scan the entire genome for variations in DNA copy number. A central task in the analysis of aCGH data is the segmentation into groups of probes sharing the same DNA copy number. Some well known segmentation methods suffer from very long running times, preventing interactive data analysis. Results: We suggest a new segmentation method based on wavelet decomposition and thresholding, which detects significant breakpoints in the data. Our algorithm is over 1,000 times faster than leading approaches, with similar performance. Another key advantage of the proposed method is its simplicity and flexibility. Due to its intuitive structure it can be easily generalized to incorporate several types of side information. Here we consider two extensions which include side information indicating the reliability of each measurement, and compensating for a changing variability in the measurement noise. The resulting algorithm outperforms existing methods, both in terms of speed and performance, when applied on real high density CGH data. Availability: Implementation is available under software tab at: http://www.ee.technion.ac.il/Sites/People/YoninaEldar/ Contact: yonina@ee.technion.ac.il
The inv dup (15) or idic (15) syndrome (Tetrasomy 15q)
Agatino Battaglia
Orphanet Journal of Rare Diseases , 2008, DOI: 10.1186/1750-1172-3-30
Abstract: Chromosome region 15q11q13, known for its instability, is highly susceptible to clinically relevant genomic rearrangements, such as supernumerary marker chromosomes formed by the inverted duplication of proximal chromosome 15. Inv dup(15) results in tetrasomy 15p and partial tetrasomy 15q. The large rearrangements, containing the Prader-Willi/Angelman syndrome critical region (PWS/ASCR), are responsible for the inv dup(15) or idic(15) syndrome. Diagnosis is achieved by standard cytogenetics and FISH analysis, using probes both from proximal chromosome 15 and from the PWS/ASCR. Microsatellite analysis on parental DNA or methylation analysis on the proband DNA, are also needed to detect the parent-of-origin of the inv dup(15) chromosome. Array CGH has been shown to provide a powerful approach for identifying and detecting the extent of the duplication. The possible occurrence of double supernumerary isodicentric chromosomes derived from chromosome 15, resulting in partial hexasomy of the maternally inherited PWS/ASCR, should be considered in the differential diagnosis. Large idic(15) are nearly always sporadic. Antenatal diagnosis is possible. Management of inv dup(15) includes a comprehensive neurophysiologic and developmental evaluation. Survival is not significantly reduced.The inv dup(15) or idic(15) syndrome can also be termed "tetrasomy 15q". About 160 patients have been reported in the medical literature [1-5].The inv dup(15) or idic(15) syndrome (inverted duplication of proximal chromosome 15 or isodicentric 15 chromosome) displays distinctive clinical findings represented by early central hypotonia, developmental delay and intellectual disability, epilepsy, and autistic behavior. The latter is characterized by lack of social interaction, non-functional use of objects, primordial type of exploration, stereotypies, absent or very poor echolalic language, limited comprehension, and poor intention to communicate. Physically, there are only minor anomalies. Altoge
Joint segmentation of many aCGH profiles using fast group LARS  [PDF]
Kevin Bleakley,Jean-Philippe Vert
Quantitative Biology , 2009,
Abstract: Array-Based Comparative Genomic Hybridization (aCGH) is a method used to search for genomic regions with copy numbers variations. For a given aCGH profile, one challenge is to accurately segment it into regions of constant copy number. Subjects sharing the same disease status, for example a type of cancer, often have aCGH profiles with similar copy number variations, due to duplications and deletions relevant to that particular disease. We introduce a constrained optimization algorithm that jointly segments aCGH profiles of many subjects. It simultaneously penalizes the amount of freedom the set of profiles have to jump from one level of constant copy number to another, at genomic locations known as breakpoints. We show that breakpoints shared by many different profiles tend to be found first by the algorithm, even in the presence of significant amounts of noise. The algorithm can be formulated as a group LARS problem. We propose an extremely fast way to find the solution path, i.e., a sequence of shared breakpoints in order of importance. For no extra cost the algorithm smoothes all of the aCGH profiles into piecewise-constant regions of equal copy number, giving low-dimensional versions of the original data. These can be shown for all profiles on a single graph, allowing for intuitive visual interpretation. Simulations and an implementation of the algorithm on bladder cancer aCGH profiles are provided.
Flexible and Accurate Detection of Genomic Copy-Number Changes from aCGH  [PDF]
Oscar M Rueda ,Ramón Díaz-Uriarte
PLOS Computational Biology , 2007, DOI: 10.1371/journal.pcbi.0030122
Abstract: 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.
Genome-Wide High-Resolution aCGH Analysis of Gestational Choriocarcinomas  [PDF]
Henriette Poaty, Philippe Coullin, Jean Félix Peko, Philippe Dessen, Ange Lucien Diatta, Alexander Valent, Eric Leguern, Sophie Prévot, Charles Gombé-Mbalawa, Jean-Jacques Candelier, Jean-Yves Picard, Alain Bernheim
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0029426
Abstract: Eleven samples of DNA from choriocarcinomas were studied by high resolution CGH-array 244 K. They were studied after histopathological confirmation of the diagnosis, of the androgenic etiology and after a microsatellite marker analysis confirming the absence of contamination of tumor DNA from maternal DNA. Three cell lines, BeWo, JAR, JEG were also studied by this high resolution pangenomic technique. According to aCGH analysis, the de novo choriocarcinomas exhibited simple chromosomal rearrangements or normal profiles. The cell lines showed various and complex chromosomal aberrations. 23 Minimal Critical Regions were defined that allowed us to list the genes that were potentially implicated. Among them, unusually high numbers of microRNA clusters and imprinted genes were observed.
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