Ontology highlight
ABSTRACT:
PROVIDER: PRJNA990836 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We detected fusion genes in 274 fresh surgical samples of gliomas using whole transcriptome sequencing. Using this approach we screened a panel of glioma samples and identified a number of activating novel fusion transcripts. Fusion detection in 274 glioma patients
2014-07-20 | E-GEOD-48865 | biostudies-arrayexpress
Project description:Agilent whole exome hybridisation capture was performed on genomic DNA derived from Chondrosarcoma cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products.
2016-05-17 | E-ERAD-37 | biostudies-arrayexpress
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. DNA copy number profiles of mouse squamous cell lung cancer (SCLC) were generated with ENCODER from whole exome sequencing data and compared to results from the NimbleGen array
2014-08-12 | E-GEOD-60254 | biostudies-arrayexpress
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. DNA copy number profiles of melanoma PDX sample were generated with ENCODER from whole exome sequencing data and compared to results from the SNP6 platform.
2014-08-12 | E-GEOD-60168 | biostudies-arrayexpress
Project description:With the whole genome SNP array information obtained from tumor and matched normal control, we could evaluate the acquired copy number alterations (CNAs) and uniparental disomies (UPDs) . Here we identified somatic mutations by whole-exome sequencing in 25 NKTCL patients and extended validation through targeted sequencing in an additional 80 cases.
2015-05-29 | GSE69382 | 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:We developed an enrichment-free, metabolic-based assay for rapid detection of tumor cells in the pleural effusion and peripheral blood samples. All nucleated cells are plated on microwell chips that contain 200,000 addressable microwells and then screened the chips. After candidate tumor cells were identified, retrieved single tumor cells with micromanipultor. To detection and analysis molecular characterization of these circulating tumor cells, we performed single cell whole genome amplification with multiple displacement amplification (MDA) technology and whole exome sequencing.
2017-02-17 | E-MTAB-4948 | biostudies-arrayexpress
Project description:Of the multiple anatomical sites represented in oral cancer, squamous cell carcinoma of the tongue (TSCC) shows the highest incidence among younger age group. Chewing betel leaf, areca nut & slaked lime and smoking tobacco are common practises in India which have direct clinical implication in TSCC carcinogenesis. Here, for the first time we define the landscape of genomic alterations in TSCC from the Indian diaspora which would help to identify novel therapeutic targets for clinical intervention and define the genetic basis for TSCC. We performed high throughput sequencing of fifty four tongue samples using whole exome sequencing (n=47, 23 paired normal tumor and 1 unpaired) and transcriptome sequencing (n=17, 10 tumor and 5 normal). Mutation, copy number analysis were carried out using exome sequencing data and transcriptome analysis provided expressed genes and transcript fusions in tongue cancer patients. Further, integrated analysis were performed to identify biologically relevant alterations. Our preliminary analysis revealed presence of most frequently altered mutations in TSCC which includes mutations in TP53, NOTCH1, CDKN2A, USP6, KMT2D etc, consistent with literature. We observed high frequency of CG/T(GC/A) transversions in non-CpG islands, a signature associated with tobacco exposure. Somatic copy number analysis revealed copy number gain in known hallmarks such as CCND1, MYC, ORAOV1 genes along with copy number alteration in novel genes. Significant positive correlation was observed in the genes harbouring copy number gains and showing increased expression.
2018-05-31 | E-MTAB-4654 | biostudies-arrayexpress
Project description:Of the multiple anatomical sites represented in oral cancer, squamous cell carcinoma of the tongue (TSCC) shows the highest incidence among younger age group. Chewing betel leaf, areca nut & slaked lime and smoking tobacco are common practises in India which have direct clinical implication in TSCC carcinogenesis. Here, for the first time we define the landscape of genomic alterations in TSCC from the Indian diaspora which would help to identify novel therapeutic targets for clinical intervention and define the genetic basis for TSCC. We performed high throughput sequencing of fifty four tongue samples using whole exome sequencing (n=47, 23 paired normal tumor and 1 unpaired) and transcriptome sequencing (n=17, 10 tumor and 5 normal). Mutation, copy number analysis were carried out using exome sequencing data and transcriptome analysis provided expressed genes and transcript fusions in tongue cancer patients. Further, integrated analysis were performed to identify biologically relevant alterations. Our preliminary analysis revealed presence of most frequently altered mutations in TSCC which includes mutations in TP53, NOTCH1, CDKN2A, USP6, KMT2D etc, consistent with literature. We observed high frequency of CG/T(GC/A) transversions in non-CpG islands, a signature associated with tobacco exposure. Somatic copy number analysis revealed copy number gain in known hallmarks such as CCND1, MYC, ORAOV1 genes along with copy number alteration in novel genes. Significant positive correlation was observed in the genes harbouring copy number gains and showing increased expression.
2018-05-31 | E-MTAB-4653 | biostudies-arrayexpress