DCEG Imputation Reference Dataset
Ontology highlight
ABSTRACT: We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.
SECONDARY ACCESSION(S): PRJNA75847PRJNA75845
REPOSITORIES: dbGaP
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Project description:<p>We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.</p>
| phs000396.v1.p1 | EGA
Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.
2011-06-13 | GSE27923 | GEO
Project description:Goal: To identify copy number variation in normal individuals using high density, non-polymorphic oligonucleotide probes Background DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1kb to over 3Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay. Results In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3M independent NspI restriction enzyme fragments in the 200bp to 1100bp size range, which is a several fold increase in marker density as compared to the 500K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries. Conclusions Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization. A set of five genomic DNA samples containing different numbers of X chromosomes (1X to 5X sample set, including NA15510 and NA10851) were hybridized to Nsp copy number (CN) arrays in triplicate to evaluate detection of copy number variation using high density, non-polymorphic oligonucleotide probes. 6 Hapmap samples were hybridized to Nsp CN arrays to evaluate Mendelian inheritance of CNVs.
2008-04-24 | E-GEOD-9053 | biostudies-arrayexpress
Project description:In this study, authors had briefly talked about the comparison of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) for binary classification of cancer. It is concluded that, SVMs perform better on cancer prediction which are not expressed by their genotype whereas ANNs capture the flaws in the other case. In this paper, the author's had provided a good strategy to construct SVM model. The model was coded from their approach and Grid Search method was used for estimation of a better set of parameters. The resulted model had provided better evaluation metrics than the one mentioned in the manuscript. The model is then exported to Open Neural Network Exchange (ONNX) format to avail the model to be accessible in various platforms thereby promoting the FAIReR (Findable, Accessible, Interoperable, Reusable, and Reproducible) protocol for sharing machine learning models. Docker files were provided for both training and testing environment so that the curator can reproduce the results.
The prediction output '0' means the sample is Benign, otherwise its Malignant.
2024-07-13 | MODEL2407130001 | BioModels
Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from peripheral blood samples. SUPPLEMENTARY FILES: CEL files were processed by manufacture's protocol. Genotype data were analyzed with the GeneSpring GT (Varia) 2.0 software package developed by Agilent Technologies (Santa Clara, CA). Matrix tables for the Genetic programs were produced (Linkage format: http://bioinformatics.med.utah.edu/~alun/software/docs/linkage.html) File 1: Matrix file_SNP_Map.txt File 2: Matrix file_Family_Information.txt File 3: Matrix file_Pedigree_Format.txt (Genotyping data of Linkage format) Transmission disequilibrium test was performed using the R program (http://www.r-project.org). File 4: Matrix file_results.txt
2011-06-13 | E-GEOD-27923 | biostudies-arrayexpress
Project description:The Pacific oyster (Crassostrea gigas) is a kind of marine bivalve of great economic and ecological importance and is among the animals possessing the highest level of genome DNA variations. Despite large efforts made for the discovery of Pacific oyster SNPs in many research groups, challenge still remains as how to utilize SNPs in a high-throughput, transferable and economical manner. In the study, we constructed an oyster 190K SNP array with Affymetrix Axiom genotyping technology. A total of 190,420 SNPs were designed on the chip, which were selected from 54 M SNPs identified by re-sequencing of more than 400 Pacific oysters. Genotyping results from 96 wild oysters indicated that 133,984 (70.4%) SNPs were polymorphic and successfully converted on the chip. Carrying 133K polymorphic SNPs, the oyster 190K SNP array is the first high density SNP chip with the largest throughput currently in mollusc and is commercially available to the worldwide research community.
2017-03-22 | GSE94633 | GEO
Project description:A synthesized Chinese Hamster Ovary (CHO) cell genome-scale model (GeM) consisting of iCHO2291 (Yeo. et al 2020) coupled with the secretory machinery presented in iCHO2048 (Gutierrez et al. 2020). This model is the most comprehensive CHO GeM to date, boasting the highest number of genes compared to any previous CHO GeM.
2023-03-06 | MODEL2206100001 | BioModels
Project description:The female sterility mutants are ideal materials for studying the pistil development in plants. We identified a female sterility mutant (fsm) exhibiting stable inheritance, which was derived from a Chinese cabbage DH line âFTâ using the combination of isolated microspore culture and ethyl methanesulfonate (EMS) mutagenesis. Genetic analysis indicated that the phenotype of fsm was controlled by a single recessive nuclear gene. The morphological observations revealed that the differences in the floral organs were significant between fsm and its wild type âFTâ, the pistil of fsm was smaller and shorter, especially the ovary; and the degenerated ovule in the ovary may directly result in the female sterility. Comparative transcriptome analysis of âFTâ and fsm were performed using RNA-Seq. A total of 1,872 differentially expressed genes were identified between âFTâ and fsm. Of these, a number of genes involved in the ovule development were found, such as PRETTY FEW SEEDS 2 (PFS2) and temperature-induced lipocalin (TIL), and these genes were all up-regulated in the fsm vs. âFTâ comparison. Furthermore, GO and KEGG pathway enrichment analyses of DEGs suggested a variety of biological processes and metabolic pathways were significantly enriched during the pistil development. In addition, the expression patterns of eighteen DEGs were analyzed using qRT-PCR to confirm the accuracy of the RNA-seq data. A total of 31,272 single nucleotide polymorphisms (SNPs) were specifically detected in fsm, which could be directly related to the female sterility phenotype. These results contribute to increase our understanding of the molecular mechanisms of pistil development in Chinese cabbage. The RNA from the developing flower buds of a female sterility mutant (fsm) and its wild typeâFTâat the full-bloom stage in Chinese cabbage were sequenced by RNA-Seq, in triplicate.
2016-06-02 | E-GEOD-76917 | biostudies-arrayexpress
Project description:Two clones of Chinese hamster ovary (CHO) cells were cultured in 2 different chemical difined custom media. Transcriptional profile were compeared between clones and media.
2022-03-01 | GSE197570 | GEO
Project description:Cancer is predominantly a somatic disease. A mutant allele found in cancer cell genome is considered somatic when it is absent in paired normal genome and dbSNP, the most comprehensive public SNP database. However, dbSNP inadequately represents several non-Caucasian populations including that from the Indian subcontinent, posing a limitation in cancer genomic analyses of data from these populations. We present TMC-SNPdb, as the first open source freely accessible (through ANNOVAR), flexible and upgradable SNP database from whole exome data of 62 normal samples derived from cancer patients of Indian origin, representing 114,309 unique germline variants. TMC-SNPdb is presented with a companion subtraction tool that can be executed with command line option or an easy-to-use graphical user interface (GUI) with the ability to deplete additional Indian population specific SNPs over and above that possible with dbSNP and 1000 Genomes databases. Using an institutional generated whole exome data set of 132 samples of Indian origin, we demonstrate that TMC-SNPdb reduced 42%, 33% and 28% false positive somatic events post dbSNP depletion in Indian origin tongue, gallbladder, and cervical cancer samples, respectively. Beyond cancer somatic analyses, we anticipate utility of TMC-SNPdb in several Mendelian germline diseases.
2018-06-06 | E-MTAB-4618 | biostudies-arrayexpress