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ABSTRACT:
PROVIDER: PRJEB50527 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:metagenomics of Laguna Verde micribialites
| PRJEB45413 | ENA
Project description:We recruited 24 Mongolian volunteers,6 of which were T2D cases(sample T1-T6), 6 were prediabetes cases(sample P1-P6), and 12 were health cases(sample C1-C12). The metagenomic analysis of gut microbiota from the volunteers’ fecal samples was performed. We compared the microbial differences in the three groups, and analyzed the differences of the stool microbial function.
2022-07-30 | E-MTAB-11957 | biostudies-arrayexpress
Project description:Metagenomic analysis of an Iranian Hypersaline Lake microbial ecosystem
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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.
2021-07-26 | E-MTAB-9191 | biostudies-arrayexpress
Project description:Fire is a crucial event regulating the structure and functioning of many ecosystems. Yet few studies focused on how fire affects both the taxonomic and functional diversity of soil microbial communities, along with plant diversity and soil carbon (C) and nitrogen (N) dynamics. Here, we analyze these effects for a grassland ecosystem 9-months after an experimental fire at the Jasper Ridge Global Change Experiment (JRGCE) site in California, USA. Fire altered soil microbial communities considerably, with community assembly process analysis indicating that environmental selection pressure was higher in burned sites. However, a small subset of highly connected taxa were able to withstand the disturbance. In addition, fire decreased the relative abundances of most genes associated with C degradation and N cycling, implicating a slow-down of microbial processes linked to soil C and N dynamics. In contrast, fire stimulated plant growth, likely enhancing plant-microbe competition for soil inorganic N. To synthesize our findings, we performed structural equation modeling, which showed that plants but not microbial communities were responsible for the significantly higher soil respiration rates in burned sites. In conclusion, fire is well-documented to considerable alter the taxonomic and functional composition of soil microorganisms, along with the ecosystem functioning, thus arousing feedback of ecosystem responses to affect global climate.
2022-02-19 | GSE126737 | GEO
Project description:Despite the uniform mortality in pancreatic adenocarcinoma (PDAC), clinical disease heterogeneity exists with limited genomic differences. A highly aggressive tumor subtype termed basal-like was identified to show worse outcomes and higher inflammatory responses. Here, we focus on the microbial effect in PDAC progression and present a comprehensive analysis of the tumor microbiome in different PDAC subtypes. Tumors from 62 resectable PDAC patients were subjected to metagenomic sequencing and RNA-seq.
2021-08-30 | GSE172356 | GEO
Project description:Global warming substantially changes precipitation patterns in the Tibetan plateau, with projection of increased precipitation in southern and northern Tibet but decreased precipitation in the center. Understanding mechanisms of such changes in greenhouse gas emissions is of vital importance in predicting ecosystem feedbacks to climate changes. Nonetheless, it has been hampered by limited knowledge in soil microbial communities, one of the major drivers of greenhouse gas emission. Here, we report a field experiment simulating drying and wetting conditions in the Tibetan grassland. Our field site is located at the Haibei Alpine Grassland Ecosystem Research Station in the northeast of Tibet Plateau, China, and we employed GeoChip 5.0 180K to analyze microbial responses. 18 samples were collected from 3 plots in Haibei Station, with 6 replicates in each plot
2016-05-28 | E-GEOD-82006 | biostudies-arrayexpress