Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25254745_1.fastq.gz | Fastqsanger.gz | |||
| SRR25254745_2.fastq.gz | Fastqsanger.gz |
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Similar Datasets
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: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:Morus alba L. Raw protein sequence reads and sequence
2024-02-08 | PXD049451 |
Project description:We used the whole exome sequencing to analyze the off-target effect of base editing system in mouse genomic DNA, which was extracted from haploid stem cells, mouse tails of semi-cloned embryos and mutant pups. The purpose of this sequencing is to find whether there exists off-target effect in the genome. By obtaining over 100 million reads of each sample from WES, we mapped the reads to the reference data base (mm10) and calculated the numbers of SNVs and indels. After filtering out naturally-occurring variants in the SNP database (dbSNP) and excluding SNPs also found in the wild-type genome, we next compared the DNA sequences at the remaining SNP sites with the on-target sequence. The results indicated that rare off-targets events happened in tested cell and embryos.
2018-08-06 | GSE115017 | GEO
Project description:Background: Whole exome sequencing (WES) has been proven to serve as a valuable basis for various applications such as variant calling and copy number variation (CNV) analyses. For those analyses the read coverage should be optimally balanced throughout protein coding regions at sufficient read depth. Unfortunately, WES is known for its uneven coverage within coding regions due to GC-rich regions or off-target enrichment. Results: In order to examine the irregularities of WES within genes, we applied Agilent SureSelectXT exome capture on human samples and sequenced these via Illumina in 2x101 paired-end mode. As we suspected the sequenced insert length to be crucial in the uneven coverage of exome captured samples, we sheared 12 genomic DNA samples to two different DNA insert size lengths, namely 130 and 170 bp. Interestingly, although mean coverages of target regions were clearly higher in samples of 130 bp insert length, the level of evenness was more pronounced in 170 bp samples. Moreover, merging overlapping paired-end reads revealed a positive effect on evenness indicating overlapping reads as another reason for the unevenness. In addition, mutation analysis on a subset of the samples was performed. In these isogenic subclones almost twofold mutations were failed in the 130 bp samples when compared to the 170 bp samples. Visual inspection of the discarded mutation sites exposed low coverages at the sites embedded in high amplitudes of coverage depth in the affected region. Conclusions: Producing longer insert reads could be a good strategy to achieve better uniform read coverage in coding regions and hereby enhancing the effective sequencing yield to provide an improved basis for further variant calling and CNV analyses.
2016-07-28 | E-MTAB-4527 | biostudies-arrayexpress
Project description:ChIP-seq and input sequence data used in the development and evaluation of the BEADS normalization method. Examination of ChIP and input sequence reads across the worm genome
2011-05-25 | E-GEOD-29427 | biostudies-arrayexpress