Metagenome benchmark
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REPOSITORIES: ENA
Similar Datasets
Project description:This study has been created to benchmark the various submission tools.
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Project description:Embedding is the key step in single-cell Hi-C (scHi-C) analysis which relies on capturing biological meaningful heterogeneity at various levels of genome architecture. To understand the strength and limitations of existing tools in various applications, here we use ten scHi-C datasets to benchmark thirteen embedding tools including Va3DE, a new convolutional neural network model that can accommodate large cell numbers. We built a software framework to decouple the preprocessing options of existing tools and found that no single tool works best across all datasets under default settings. The difficulty levels and preferred resolutions are different between benchmark datasets, and the choice of data representation and preprocessing strongly impact the embedding performance. Embedding cells from early embryonic stages relies on long-range compartment-scale contacts, but resolving cell cycle phases and complex tissue requires short-range loop-scale contacts. Both random-walk and inverse document frequency (IDF) transformation prefers long-range “compartment-scale” over short-range “loop-scale” embedding, while deep-learning methods better overcome sparsity at both scales and are more versatile with different resolutions. Finally, “diagonal integration” with independent data modal is a promising approach to distinguish similar cell subpopulations. Our findings underscore the significance of appropriate priors for scHi-C embedding and offer new insights into genome architecture heterogeneity.
2025-08-19 | GSE305523 | GEO
Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.
2025-06-15 | GSE298403 | GEO
Project description:Generate benchmark data for scPLATE-Seq
2021-11-11 | GSE104493 | GEO
Project description:Hartwig Medical Foundation Benchmark Set
| PRJEB33197 | ENA
Project description:Benchmark Data for scPLATE-Seq
| PRJNA412850 | ENA
Project description:Nanopore R10.4.1 Sequencing Benchmark Data
| PRJEB64652 | ENA
Project description:Dietary intake of fruits and vegetables (FV) has been inversely associated with lower risk of ulcerative colitis. A pig model was used to evaluate the impact of feeding FV on the host response to dextran sulfate sodium (DSS)-induced colitis. Methods: Six-week-old pigs were fed a grower diet alone or supplemented with lyophilized FV equivalent to the half (half-FV) or full (full-FV) daily levels recommended for humans by the Dietary Guidelines for Americans (DGA). Pigs were fed a 1) grower diet alone (negative control), 2) grower diet and orally treated with 4% DSS for 10 days to induce colitis (positive control), 3) half-FV diet treated with 4% DSS or 4) full-FV diet treated with 4% DSS. Pigs were monitored for the development of clinical signs of colitis. Proximal colon (PC) contents and mucosa (PCM) were collected for gut metagenome, tissue transcriptome and histopathological analysis. Results: Pigs fed the full-FV diet did not exhibit diarrhea, showed less fecal occult blood (FOB), PCM crypt hyperplasia but with no differential expressed genes (DEG) or changes in PC microbiome diversity (p < 0.05). Pigs within the half-FV group exhibited increased group FOB and DEG associated with tissue remodeling, crypt and goblet cell hyperplasia in the PCM and no changes in PC microbiome diversity and two pigs exhibiting diarrhea (p < 0.05). Pigs within the DSS positive control group exhibited a reduced DEG involved with intestinal immune response and PC microbiome diversity with altered metagenome, increased group PCM erosion and FOB with persistent diarrhea in one pig (p < 0.05) Conclusions: Overall, our results showed that pigs fed a three-week full-FV supplemented diet, were resistant to DSS-induced colitis with a differential dose-dependent protective effect on host intestinal tissue and gut metagenome when exposed to an inflammatory challenge.
2026-04-01 | GSE317287 | GEO
Project description:Real patient variability Benchmark Dataset for Optimization of DIA data analysis workflows
| EGAD00010002223 | EGA
Project description:Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.
| S-EPMC5903868 | biostudies-literature