Affymetrix SNP copy number data for embryonic stem cell samples
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE64241 | GEO | 2014/12/17
SECONDARY ACCESSION(S): PRJNA270524
REPOSITORIES: GEO
Similar Datasets
Project description:Human pluripotent stem cell (hPSC) lines exhibit repeated patterns of genetic variation, which can alter in vitro properties as well as suitability for clinical use. We examined associations between copy number variations (CNVs) on chromosome 17 and hPSC mesodiencephalic dopaminergic (mDA) differentiation. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from cryopreserved stem cell samples. Copy number analysis of Affymetrix Genome-Wide Human SNP Array 6.0 was performed for 17 stem cell samples.
2014-12-17 | E-GEOD-64241 | biostudies-arrayexpress
Project description:Nkx2.9 is involved in programming of mesodiencephalic dopaminergic neurons early in development.
2021-12-15 | GSE185584 | GEO
Project description:Copy number variation (CNV) and loss of heterozygosity (LOH) were investigated in adult Chinese patients with acute lymphoblastic leukemia (ALL), and these patients were screened for adult ALL prognostic genes.The most frequent CNVs are gain at chr13q, loss at chr6 and recurrent LOH at chr17p and 1p33. In Ph- B-ALL patients, the most frequent CNVs are gain at chr7, loss at chr9p and recurrent LOH at chr15q. In T-ALL, the most frequent CNVs are gain at chr20 and 7q, loss at chr2p and recurrent LOH also at chr15q.
2015-01-01 | GSE57018 | GEO
Project description:BackgroundCopy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments.ResultsAPT had median locus-level copy numbers closest to a value of two, whereas PennCNV and Aroma.Affymetrix had the smallest variability associated with the median copy number. Of those evaluated, only PennCNV provides copy number specific quality-control metrics and identified 136 poor CNV samples. Regions of copy number variation (CNV) were detected using the hidden Markov models provided within PennCNV and CRLMM/VanillaIce. PennCNV detected more CNVs than CRLMM/VanillaIce; the median number of CNVs detected per sample was 39 and 30, respectively. PennCNV detected most of the regions that CRLMM/VanillaIce did as well as additional CNV regions. The median concordance between PennCNV and CRLMM/VanillaIce was 47.9% for duplications and 51.5% for deletions. The estimated false-positive rate associated with deletions was similar for PennCNV and CRLMM/VanillaIce.ConclusionsIf the objective is to perform statistical tests on the locus-level copy number data, our empirical results suggest that PennCNV or Aroma.Affymetrix is optimal. If the objective is to perform statistical tests on the summarized segmented data then PennCNV would be preferred over CRLMM/VanillaIce. Specifically, PennCNV allows the analyst to estimate locus-level copy number, perform segmentation and evaluate CNV-specific quality-control metrics within a single software package. PennCNV has relatively small bias, small variability and detects more regions while maintaining a similar estimated false-positive rate as CRLMM/VanillaIce. More generally, we advocate that software developers need to provide guidance with respect to evaluating and choosing optimal settings in order to obtain optimal results for an individual dataset. Until such guidance exists, we recommend trying multiple algorithms, evaluating concordance/discordance and subsequently consider the union of regions for downstream association tests.
| S-EPMC3146450 | biostudies-literature
Project description:MotivationCurrent algorithms for estimating DNA copy numbers (CNs) borrow concepts from gene expression analysis methods. However, single nucleotide polymorphism (SNP) arrays have special characteristics that, if taken into account, can improve the overall performance. For example, cross hybridization between alleles occurs in SNP probe pairs. In addition, most of the current CN methods are focused on total CNs, while it has been shown that allele-specific CNs are of paramount importance for some studies. Therefore, we have developed a summarization method that estimates high-quality allele-specific CNs.ResultsThe proposed method estimates the allele-specific DNA CNs for all Affymetrix SNP arrays dealing directly with the cross hybridization between probes within SNP probesets. This algorithm outperforms (or at least it performs as well as) other state-of-the-art algorithms for computing DNA CNs. It better discerns an aberration from a normal state and it also gives more precise allele-specific CNs.AvailabilityThe method is available in the open-source R package ACNE, which also includes an add on to the aroma.affymetrix framework (http://www.aroma-project.org/).
| S-EPMC2913655 | biostudies-literature
Project description:Induced pluripotent stem cells (iPSCs) harbor great promise for in vitro generation of disease-relevant cell types, such as mesodiencephalic dopaminergic (mdDA) neurons involved in Parkinson’s disease. Although iPSC-derived midbrain DA neurons have been generated, detailed genetic and epigenetic characterization of such neurons is still lacking. The goal of this study is to examine the authenticity of iPSC-derived DA neurons obtained by established protocols. We FACS-purified mdDA (Pitx3gfp/+) neurons derived from mouse iPSCs and primary mdDA (Pitx3gfp/+) neurons to analyze and compare their genetic and epigenetic features. Although iPSC-derived DA neurons largely adopt characteristics of their in-vivo counterparts, relevant deviations in global gene expression and DNA methylation were found. Hypermethylated genes, mainly involved in neurodevelopment and basic neuronal functions, consequently showed reduced expression levels. Such abnormalities should be addressed as they might affect unambiguous long-term functionality and hamper the potential of iPSC-derived DA neurons for in-vitro disease modeling or cell-based therapy. RRBS methylation maps were generated for iPSCs cells, dopaminergic neurons derived from iPSCs and primary mesodiencephalic dopaminergic neurons
2014-03-01 | E-GEOD-55475 | biostudies-arrayexpress
Project description:Lung cancer is the leading cause of death from malignant diseases worldwide, with the non-small cell (NSCLC) subtype accounting for the majority of cases. NSCLC is characterized by frequent genomic imbalances and copy number variations (CNVs), but the epigenetic aberrations that are associated with clinical prognosis and therapeutic failure remain not completely identify. In the present study, a total of 55 lung cancer patients were included and we conducted genomic and genetic expression analyses, immunohistochemical protein detection, DNA methylation and chromatin immunoprecipitation assays to obtain genetic and epigenetic profiles associated to prognosis and chemoresponse of NSCLC patients. Finally, siRNA transfection-mediated genetic silencing and cisplatinum cellular cytotoxicity assays in NSCLC cell lines A-427 and INER-37 were assesed to described chemoresistance mechanisms involved. Our results identified high frequencies of CNVs (60% of cases) in the 7p22.3-p21.1 and 7p15.3-p15.2 cytogenetic regions. However, overexpression of genes, such as MEOX2, HDAC9, TWIST1 and AhR, at 7p21.2-p21.1 locus occurred despite the absence of CNVs and little changes in DNA methylation. In contrast, the promoter sequences of MEOX2 and TWIST1 displayed significantly lower/decrease in the repressive histone mark H3K27me3 and increased in the active histone mark H3K4me3 levels. Finally these results correlate with poor survival in NSCLC patients and cellular chemoresistance to oncologic drugs in NSCLC cell lines in a MEOX2 and TWIST1 overexpression dependent-manner. In conclusion, we report for the first time that MEOX2 participates in chemoresistance irrespective of high CNV, but it is significantly dependent upon H3K27me3 enrichment probably associated with aggressiveness and chemotherapy failure in NSCLC patients, however additional clinical studies must be performed to confirm our findings as new probable clinical markers in NSCLC patients.
2014-12-10 | GSE62407 | GEO
Project description:BackgroundAffymetrix SNP arrays can interrogate thousands of SNPs at the same time. This allows us to look at the genomic content of cancer cells and to investigate the underlying events leading to cancer. Genomic copy-numbers are today routinely derived from SNP array data, but the proposed algorithms for this task most often disregard the genotype information available from germline cells in paired germline-tumour samples. Including this information may deepen our understanding of the "true" biological situation e.g. by enabling analysis of allele specific copy-numbers. Here we rely on matched germline-tumour samples and have developed a Hidden Markov Model (HMM) to estimate allelic copy-number changes in tumour cells. Further with this approach we are able to estimate the proportion of normal cells in the tumour (mixture proportion).ResultsWe show that our method is able to recover the underlying copy-number changes in simulated data sets with high accuracy (above 97.71%). Moreover, although the known copy-numbers could be well recovered in simulated cancer samples with more than 70% cancer cells (and less than 30% normal cells), we demonstrate that including the mixture proportion in the HMM increases the accuracy of the method. Finally, the method is tested on HapMap samples and on bladder and prostate cancer samples.ConclusionThe HMM method developed here uses the genotype calls of germline DNA and the allelic SNP intensities from the tumour DNA to estimate allelic copy-numbers (including changes) in the tumour. It differentiates between different events like uniparental disomy and allelic imbalances. Moreover, the HMM can estimate the mixture proportion, and thus inform about the purity of the tumour sample.
| S-EPMC2206057 | biostudies-literature
Project description:The progressive mechanism of myelodysplastic syndrome (MDS) remains unknown. We report that ROBO1 and ROBO2 are identified as novel progression-related somatic mutations using whole-exome and targeted sequencing in six of 16 (37.5%) paired MDS patients undergoing disease progression. To investigated the effect of ROBO1 or ROBO2 on ROBO1/2 CN number and LOH, we employed a Cytosan 750K chip to analyze the copy-number variations (CNVs) and loss of heterogeneity (LOH) in MDS patients with ROBO1&2 mutations.
2015-09-15 | GSE73005 | GEO
Project description:Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans.By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings.The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.
| S-EPMC4518889 | biostudies-literature