Ontology highlight
ABSTRACT:
PROVIDER: PRJNA814051 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:DNA WGS Long Read Sequence (PromethION) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"
| EGAD00001015400 | EGA
Project description:Mycobacterium tuberculosis genome sequencing for variant calling benchmarking
| PRJNA719670 | ENA
Project description:DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"
| EGAD00001015399 | EGA
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:Benchmarking ultra-high molecular weight DNA preservation methods for long-read and long-range sequencing
| PRJDB13233 | ENA
Project description:Although most disease associations detected by GWAS are nongenic, very few have been mapped to causal regulatory variants. Here, we present a method for detecting regulatory QTLs that does not require genotyping or whole-genome sequencing. The method combines deep, long-read ChIP-seq with a new statistical test that simultaneously scores peak height correlation and allelic imbalance: the Genotype-independent Signal Correlation and Imbalance (G-SCI) test. We performed histone acetylation ChIP-seq on 57 human lymphoblastoid cell lines and used the resulting reads to call 500,066 SNPs de novo within regulatory elements. The G-SCI test annotated 8,764 of these as histone acetylation QTLs (haQTLs) - an order of magnitude larger than the set of candidates detected by expression QTL analysis. Lymphoblastoid haQTLs were highly predictive of autoimmune disease mechanisms. Thus, our method facilitates large-scale regulatory variant detection in any moderately-sized cohort for which functional profiling data can be generated, thus simplifying identification of causal variants within GWAS loci. We applied our method, named Regulatory Variant Ascertainment and chromatin Regression by sequencing (RegVAR-seq), to 57 cell lines from a single population group. We used the resulting sequence data for variant calling, and validated calls using an independent platform. We then identified histone acetylation QTLs (haQTLs) using a novel statistical test that requires no prior genotype information and combines peak height and allelic imbalance data across the 57 individuals. Transcription factor binding site analysis was used to independently support the functionality of haQTLs. Finally, we examined the association between haQTLs and SNPs associated with human phenotypes.
2015-03-01 | E-GEOD-58852 | biostudies-arrayexpress
Project description:Natural mitochondrial DNA (mtDNA) sequence variation plays a fundamental role in human disease and enables the clonal tracing of native human cells. While various genotyping approaches revealed mutational heterogeneity in human tissues and single cells, current methodologies are limited by scale. Here, we introduce a high-throughput, droplet-based mitochondrial single-cell Assay for Transposase Accessible Chromatin with sequencing (mtscATAC-seq) protocol and computational framework that facilitate high-confidence mtDNA mutation calling in thousands of single cells. Further, the concomitant high-quality accessible chromatin readout enables the paired inference of individual cell mtDNA heteroplasmy, clonal lineage, cell state, and accessible chromatin regulatory features. Our multi-omic analyses reveals single-cell variation in heteroplasmy of a pathologic mtDNA variant (m.8344A>G), which we tie to intra-individual chromatin variability and clonal evolution. Further, using somatic mtDNA mutations, we clonally trace thousands of hematopoietic cells in vitro and in patients with chronic lymphocytic leukemia, linking epigenomic variability to subclonal evolution in vivo.
2020-07-13 | GSE142740 | GEO
Project description:Natural mitochondrial DNA (mtDNA) sequence variation plays a fundamental role in human disease and enables the clonal tracing of native human cells. While various genotyping approaches revealed mutational heterogeneity in human tissues and single cells, current methodologies are limited by scale. Here, we introduce a high-throughput, droplet-based mitochondrial single-cell Assay for Transposase Accessible Chromatin with sequencing (mtscATAC-seq) protocol and computational framework that facilitate high-confidence mtDNA mutation calling in thousands of single cells. Further, the concomitant high-quality accessible chromatin readout enables the paired inference of individual cell mtDNA heteroplasmy, clonal lineage, cell state, and accessible chromatin regulatory features. Our multi-omic analyses reveals single-cell variation in heteroplasmy of a pathologic mtDNA variant (m.8344A>G), which we tie to intra-individual chromatin variability and clonal evolution. Further, using somatic mtDNA mutations, we clonally trace thousands of hematopoietic cells in vitro and in patients with chronic lymphocytic leukemia, linking epigenomic variability to subclonal evolution in vivo.
2020-07-13 | GSE142743 | GEO