Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1168556 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To explore the genetic cause of a Chinese woman with fetal hydrocephalus X-linked hydrocephalus (XLH), a genetic disorder, has an incidence of 1/30,000 male births. The great proportion of XLH is ascribed to loss of function mutations of L1 cell adhesion molecule gene (L1CAM), but silent mutations in L1CAM with pathogenic potential were rare, and were usually ignored especially in WES detection. In the present study, we describe a novel silent L1CAM mutation in a Chinese pregnant woman reporting continuous five times pregnancies with fetal hydrocephalus. After fetal blood sampling, we found c.453G>T (p.Gly151=) in L1CAM gene of the fetus by whole exome sequencing (WES), RT-PCR of the mRNA from cord blood mononuclear cells and subsequent sequence analysis identified the mutation created a potential 5' splice site consensus sequence, which would result in an in-frame deletion of 72 bp from exon 5 and 24 amino acids of the L1CAM protein. Heterozygous mutations were confirmed in analyzing DNA and mRNA from peripheral blood mononuclear cells of the woman, and, a severe L1 syndrome was confirmed by fetal ultrasound scan and MRI. Our study first indicated c.453G>T (p.Gly151=) in L1CAM could be disease causing for hydrocephalus, which would aid in genetic counseling for the prenatal diagnosis of hydrocephalus. Meanwhile, it suggested some silent mutations detected in WES should not be ignored, splicing predictions of these mutations were necessary.
2019-07-16 | GSE133063 | GEO
Project description:A large panel of 81 liver cancer cell models, designated as LIver cancer MOdel REpository (LIMORE) was constructed. These cell lines include 31 public cell lines and 50 new cell models establishend from Chinese liver cancer patients. Whole genome sequencing (WGS), exome sequencing (WES) and RNA sequencing (RNAseq) were performed to obtain the genetic information for these cell lines. These cell lines and associated data provide new models and also a rich resource for liver cancer.
2019-06-17 | GSE97098 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60254 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60168 | GEO
Project description:Ovarian cancer is a global problem, is typically diagnosed at a late stage and has no effective screening strategy. Platinum-based chemotherapy or Poly(ADP-ribose) polymerase inhibitors (PARPis) treatment are most frequently applied for ovarian cancer patients who are inoperable and in the advanced stage. The recognition of homologous recombination deficiency (HRD) as a biomarker to predict the effect of Platinum-based or PARPis treatment. WGS and WES can detect tumor HRD status but have several disadvantages which restrict their clinical application. My choice HRD CDx and Foundation Focus CDx are approved by FDA for HRD detection, however, whether they are applicable to the Chinese population or not is unknown. In this study, we created an SNP-based Tg-NGS panel to fill in gaps in Chinese patients’ HRD screening. Our results showed that the panel is cost and time-saving compared with WGS, but equivalent with SNP microarray on CNV and HRD detection. In summary, this newly developed kit is promising in clinical application to guide ovarian cancer and even other cancer types therapy.
2023-02-21 | GSE203509 | GEO
Project description:Blood samples from patients with myeloid malignancies were analyzed using whole exome sequencing (WES). Data set from genotyping by microarray of the same samples has been deposited in ArrayExpress under accession number E-MTAB-1845 (https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1845/).
2013-11-01 | E-MTAB-1850 | biostudies-arrayexpress