Multiomic analysis
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Genome Wide Association Studies (GWAS) are based on the observation of genome-wide sets of genetic variants – typically single-nucleotide polymorphisms (SNPs) – in diferent individuals that are associated with phenotypic traits.
20p vinarcissa 21-03-2023 5 1 Download
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Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed.
16p vialfrednobel 29-01-2022 8 0 Download
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Although scRNA-seq is now ubiquitously adopted in studies of intratumor heterogeneity, detection of somatic mutations and inference of clonal membership from scRNA-seq is currently unreliable. We propose DENDRO, an analysis method for scRNA-seq data that clusters single cells into genetically distinct subclones and reconstructs the phylogenetic tree relating the subclones.
15p viarchimedes 26-01-2022 6 0 Download
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Simultaneous measurements of transcriptomic and epigenomic profiles in the same individual cells provide an unprecedented opportunity to understand cell fates. However, effective approaches for the integrative analysis of such data are lacking.
19p viarchimedes 26-01-2022 8 0 Download
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The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances to extrapolate cell states.
6p viarchimedes 26-01-2022 10 0 Download
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Tumor stroma interaction is known to take a crucial role in cancer growth and progression. In the present study, it was performed gene expression analysis of stroma samples with ovarian and breast cancer through an integrative analysis framework to identify common critical biomolecules at multiomics levels. Gene expression datasets were statistically analyzed to identify common differentially expressed genes (DEGs) by comparing tumor stroma and normal stroma samples.
11p thiencuuchu 27-11-2021 9 1 Download
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There exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genomewide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multiomic modules.
13p vitzuyu2711 29-09-2021 11 1 Download
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High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise overlook.
13p vijisoo2711 27-10-2020 13 0 Download
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Studies on multiple modalities of omics data such as transcriptomics, genomics and proteomics are growing in popularity, since they allow us to investigate complex mechanisms across molecular layers. It is widely recognized that integrative omics analysis holds the promise to unlock novel and actionable biological insights into health and disease.
10p vicolorado2711 23-10-2020 15 0 Download
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Beta vulgaris L. is one of the main sugar-producing crop species and is highly adaptable to saline soil. This study explored the alterations to the carbon and nitrogen metabolism mechanisms enabling the roots of sugar beet seedlings to adapt to salinity.
21p viuchiha2711 21-04-2020 6 0 Download