Copy number (SNP) analysis from leukemic patients with complex structural variants
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE124330 | GEO | 2019/05/13
REPOSITORIES: GEO
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Project description:Structural variants can lead to an alteration of gene expression which may be associated with disease worsening. In our study we attempted to describe expression changes associated with the presence of extensive genomic rearrangements in chronic lymphocytic leukemia. We used microarrays for establishing an algorithm for identification of unique expression profiles associated with extensive genomic rearrangements.
2019-05-13 | GSE124329 | GEO
Project description:Structural variants can lead to an alteration of gene expression which may be associated with disease worsening. In our study we attempted to describe expression changes associated with the presence of extensive genomic rearrangements in chronic lymphocytic leukemia.
2019-05-13 | GSE128668 | GEO
Project description:Copy number (SNP) analysis from leukemic patients with complex structural variants
| PRJNA511662 | ENA
Project description:MotivationGenome-wide association studies (GWAS) generate relationships between hundreds of thousands of single nucleotide polymorphisms (SNPs) and complex phenotypes. The contribution of the traditionally overlooked copy number variations (CNVs) to complex traits is also being actively studied. To facilitate the interpretation of the data and the designing of follow-up experimental validations, we have developed a database that enables the sensible prioritization of these variants by combining several approaches, involving not only publicly available physical and functional annotations but also multilocus linkage disequilibrium (LD) annotations as well as annotations of expression quantitative trait loci (eQTLs).ResultsFor each SNP, the SCAN database provides: (i) summary information from eQTL mapping of HapMap SNPs to gene expression (evaluated by the Affymetrix exon array) in the full set of HapMap CEU (Caucasians from UT, USA) and YRI (Yoruba people from Ibadan, Nigeria) samples; (ii) LD information, in the case of a HapMap SNP, including what genes have variation in strong LD (pairwise or multilocus LD) with the variant and how well the SNP is covered by different high-throughput platforms; (iii) summary information available from public databases (e.g. physical and functional annotations); and (iv) summary information from other GWAS. For each gene, SCAN provides annotations on: (i) eQTLs for the gene (both local and distant SNPs) and (ii) the coverage of all variants in the HapMap at that gene on each high-throughput platform. For each genomic region, SCAN provides annotations on: (i) physical and functional annotations of all SNPs, genes and known CNVs within the region and (ii) all genes regulated by the eQTLs within the region.Availabilityhttp://www.scandb.org.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC2852202 | biostudies-literature
Project description:Ebstein anomaly (EA) is a rare congenital defect characterized by apical displacement of the septal tricuspid leaflets and atrialization of the right ventricle. The etiology of EA is unclear; however, recurrence in families and the association of EA with genetic syndromes and copy number variants (CNVs) suggest a genetic component.We performed a population-based study to search for recurrent and novel CNVs in a previously unreported set of EA cases.We genotyped 60 EA cases identified from all live births (2,891,076) from selected California counties (1991-2010) using the Illumina HumanOmni2.5-8 array. We identified 38 candidate CNVs in 28 (46%) cases and prioritized and validated 11 CNVs based on the genes included.Five CNVs (41%) overlapped or were close to genes involved in early myocardial development, including NODAL, PDLIM5, SIX1, ASF1A and FGF12. We also replicated a previous association of EA with CNVs at 1p34.1 and AKAP12. Finally, we identified four CNVs overlapping or in close proximity to the transcription factors HES3, TRIM71, CUX1 and EIF4EBP2.This study supports the relationship of genetic factors to EA and demonstrates that defects in cardiomyocytes and myocardium differentiation may play a role. Abnormal differentiation of cardiomyocytes and how genetic factors contribute should be examined for their association with EA.
| S-EPMC5720705 | biostudies-other
Project description:Structural variations, including recurrent Copy Number Variants (CNVs) at specific genomic loci, have been found to be associated with increased risk of several diseases and syndromes. CNV carrier status can be determined in large collections of samples using SNP arrays and, more recently, sequencing data. Although there is some consensus among researchers about the essential steps required in such analysis (i.e., CNV calling, filtering of putative carriers, and visual validation using intensity data plots of the genomic region), standard methodologies and processes to control the quality and consistency of the results are lacking. Here, we present a comprehensive and user-friendly protocol that we have refined from our extensive research experience in the field. We cover every aspect of the analysis, from input data curation to final results. For each step, we highlight which parameters affect the analysis the most and how different settings may lead to different results. We provide a pipeline to run the complete analysis with effective (but customizable) pre-sets. We present software that we developed to better handle and filter putative CNV carriers and perform visual inspection to validate selected candidates. Finally, we describe methods to evaluate the critical sections and actions to counterbalance potential problems. The current implementation is focused on Illumina SNP array data. All the presented software is freely available and provided in a ready-to-use docker container. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: From raw intensity data files to CNV calls Basic Protocol 2: From CNV calls to validated CNV carriers. Basic Protocol 3: Quality control and quality assessment Basic Protocol 4: Install the necessary software.
| S-EPMC9729012 | biostudies-literature
Project description:Discovery of common Asian copy number variants using a novel integrated high-resolution array CGH and massively parallel DNA sequencing. We attempted to discover common Asian copy number variants (CNVs) from the DNA of 30 Asian women (10 Korean, 10 CHB (HapMap), 10 JPT (HapMap)) using a custom-designed 24M-oligonucleotide Agilent platform (1.1M X 24 slides). The reference sample for aCGH was NA10851 (HapMap CEPH). In addition to the 30 women, 3 more individuals were analyzed as controls (AK1 (Kim, J.I. et al., 2009 Nature), NA12878 and NA19240).
2010-01-13 | GSE19651 | GEO
Project description:BackgroundIn studies of case-parent trios, we define copy number variants (CNVs) in the offspring that differ from the parental copy numbers as de novo and of interest for their potential functional role in disease. Among the leading array-based methods for discovery of de novo CNVs in case-parent trios is the joint hidden Markov model (HMM) implemented in the PennCNV software. However, the computational demands of the joint HMM are substantial and the extent to which false positive identifications occur in case-parent trios has not been well described. We evaluate these issues in a study of oral cleft case-parent trios.ResultsOur analysis of the oral cleft trios reveals that genomic waves represent a substantial source of false positive identifications in the joint HMM, despite a wave-correction implementation in PennCNV. In addition, the noise of low-level summaries of relative copy number (log R ratios) is strongly associated with batch and correlated with the frequency of de novo CNV calls. Exploiting the trio design, we propose a univariate statistic for relative copy number referred to as the minimum distance that can reduce technical variation from probe effects and genomic waves. We use circular binary segmentation to segment the minimum distance and maximum a posteriori estimation to infer de novo CNVs from the segmented genome. Compared to PennCNV on simulated data, MinimumDistance identifies fewer false positives on average and is comparable to PennCNV with respect to false negatives. Genomic waves contribute to discordance of PennCNV and MinimumDistance for high coverage de novo calls, while highly concordant calls on chromosome 22 were validated by quantitative PCR. Computationally, MinimumDistance provides a nearly 8-fold increase in speed relative to the joint HMM in a study of oral cleft trios.ConclusionsOur results indicate that batch effects and genomic waves are important considerations for case-parent studies of de novo CNV, and that the minimum distance is an effective statistic for reducing technical variation contributing to false de novo discoveries. Coupled with segmentation and maximum a posteriori estimation, our algorithm compares favorably to the joint HMM with MinimumDistance being much faster.
| S-EPMC3576329 | biostudies-literature
Project description:Charcot-Marie-Tooth disease type 1A (CMT1A) is caused by an abnormal copy number variation (CNV) with a trisomy of chromosome 17p12. The increase of the DNA-segment copy number is expected to alter the allele frequency of single nucleotide polymorphism (SNP) within the duplicated region. We tested whether SNP allele frequency determined by a Sequenom MassArray can be used to detect the CMT1A mutation. Our results revealed distinct patterns of SNP allele frequency distribution, which reliably differentiated CMT1A patients from controls. This finding suggests that this technique may serve as an alternative approach to identifying CNV in certain diseases, including CMT1A.
| S-EPMC4254366 | biostudies-literature
Project description:BackgroundGenotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets.ResultsHere we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs.ConclusionOur new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.
| S-EPMC3464625 | biostudies-literature