Shotgun metagenome sequencing
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1020264 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Part of a set of highly integrated epigenome maps for Arabidopsis thaliana. Keywords: Illumina high-throughput bisulfite sequencing Whole genome shotgun bisulfite sequencing of wildtype Arabidopsis plants (Columbia-0), and met1, drm1 drm2 cmt3, and ros1 dml2 dml3 null mutants using the Illumina Genetic Analyzer.
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Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9189 | biostudies-arrayexpress
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
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Project description:Rapid advances in high-throughput DNA sequencing technologies are accelerating the pace of research into personalized medicine. While methods for variant discovery and genotyping from whole genome sequencing (WGS) datasets have been well established, linking variants together into a single haplotype remains a challenge. An understanding of complete haplotypes of an individual will help clarify the consequences of inheriting multiple alleles in combination, identify novel disease associations, and augment studies of gene regulation. Although numerous methods have been developed to reconstruct haplotypes from WGS data, chromosome-span haplotypes at high resolution have been difficult to obtain. Here we present a novel method to accurately reconstruct chromosome-span haplotypes from proximity-ligation and DNA shotgun sequencing. We demonstrate the utility of this approach in producing high-resolution chromosome-span haplotype phasing in mouse and human. While proximity-ligation based methods were originally designed to investigate spatial organization of the genome, our results lend support for their use as a general tool for haplotyping in the future.
2013-11-03 | GSE48592 | GEO
Project description:Genomic shotgun sequences of Trypanosoma brucei brucei from Uganda with minimal laboratory passage.
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Project description:Rapid advances in high-throughput DNA sequencing technologies are accelerating the pace of research into personalized medicine. While methods for variant discovery and genotyping from whole genome sequencing (WGS) datasets have been well established, linking variants together into a single haplotype remains a challenge. An understanding of complete haplotypes of an individual will help clarify the consequences of inheriting multiple alleles in combination, identify novel disease associations, and augment studies of gene regulation. Although numerous methods have been developed to reconstruct haplotypes from WGS data, chromosome-span haplotypes at high resolution have been difficult to obtain. Here we present a novel method to accurately reconstruct chromosome-span haplotypes from proximity-ligation and DNA shotgun sequencing. We demonstrate the utility of this approach in producing high-resolution chromosome-span haplotype phasing in mouse and human. While proximity-ligation based methods were originally designed to investigate spatial organization of the genome, our results lend support for their use as a general tool for haplotyping in the future. Hi-C experiments in two replicates of Human GM12878 Lymphoblastoid cells and two replicates of F123 mouse ES cells (4 total samples)
2013-11-03 | E-GEOD-48592 | biostudies-arrayexpress
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