Motivation: Metagenomics leads to major advances in microbial ecology and biologists need user friendly tools to analyze their data on their own.
Results: This Galaxy-supported pipeline, called FROGS, is designed to analyze large sets of amplicon sequences and produce abundance tables of Operational Taxonomic Units (OTUs) and their taxonomic affiliation. The clustering uses Swarm. The chimera removal uses VSEARCH, combined with original cross-sample validation. The taxonomic affiliation returns an innovative multi-affiliation output to highlight databases conflicts and uncertainties. Statistical results and numerous graphical illustrations are produced along the way to monitor the pipeline. FROGS was tested for the detection and quantification of OTUs on real and in silico datasets and proved to be rapid, robust and highly sensitive. It compares favorably with the widespread mothur, UPARSE and QIIME.
Availability And Implementation: Source code and instructions for installation: https://github.com/geraldinepascal/FROGS.git. A companion website: http://frogs.toulouse.inra.fr.
Contact: geraldine.pascal@inra.fr.
Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btx791 | DOI Listing |
BMC Med Inform Decis Mak
January 2025
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Background: The diagnosis and treatment of epilepsy continue to face numerous challenges, highlighting the urgent need for the development of rapid, accurate, and non-invasive methods for seizure detection. In recent years, advancements in the analysis of electroencephalogram (EEG) signals have garnered widespread attention, particularly in the area of seizure recognition.
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Sci Rep
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Department of Orthopaedics, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu, China.
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Neuroblastoma (NB) remains associated with high mortality and low initial response rate, especially for high-risk patients, thus warranting exploration of molecular markers for precision risk classifiers. Through integrating multiomics profiling, we identified a range of hub genes involved in cell cycle and associated with dismal prognosis and malignant cells. Single-cell transcriptome sequencing revealed that a subset of malignant cells, subcluster 1, characterized by high proliferation and dedifferentiation, was strongly correlated with the hub gene signature and orchestrated an immunosuppressive tumor microenvironment (TME).
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