Background: With next-generation sequencing (NGS) technologies, the life sciences face a deluge of raw data. Classical analysis processes for such data often begin with an assembly step, needing large amounts of computing resources, and potentially removing or modifying parts of the biological information contained in the data. Our approach proposes to focus directly on biological questions, by considering raw unassembled NGS data, through a suite of six command-line tools.
Findings: Dedicated to 'whole-genome assembly-free' treatments, the Colib'read tools suite uses optimized algorithms for various analyses of NGS datasets, such as variant calling or read set comparisons. Based on the use of a de Bruijn graph and bloom filter, such analyses can be performed in a few hours, using small amounts of memory. Applications using real data demonstrate the good accuracy of these tools compared to classical approaches. To facilitate data analysis and tools dissemination, we developed Galaxy tools and tool shed repositories.
Conclusions: With the Colib'read Galaxy tools suite, we enable a broad range of life scientists to analyze raw NGS data. More importantly, our approach allows the maximum biological information to be retained in the data, and uses a very low memory footprint.
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http://dx.doi.org/10.1186/s13742-015-0105-2 | DOI Listing |
J Am Mosq Control Assoc
December 2024
U.S. Centers for Disease Control and Prevention, Division of Vector-Borne Diseases, 3156 Rampart Road, Fort Collins, CO 80521.
The tools available to vector control districts (VCDs) to collect mosquito surveillance data are constantly evolving. As more VCDs obtain real-time polymerase chain reaction (PCR) instruments and the costs associated with computing power and next-generation sequencing continue to decrease, the option of generating useful molecular data in-house becomes more viable. Measures such as arbovirus testing and genotyping for insecticide resistance mutations using RT-qPCR, and identifying species used for mosquito bloodmeals with next-generation sequencing or Sanger sequencing are examples.
View Article and Find Full Text PDFBioinform Adv
November 2024
Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, 06466, Germany.
Motivation: The Galaxy workflow system is an open-source platform supporting data-intensive research in life sciences, featuring a user-friendly web interface for complex analyses without extensive programming. It also offers a representational state transfer based API, enabling remote execution of specific tools. Galaxy supports similarity searches for nucleotide and amino acid sequences, with integrated tools like NCBI BLAST+ and DIAMOND.
View Article and Find Full Text PDFBioinformatics
November 2024
Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY.
Summary: LEfSe is a widely used Python package and Galaxy module for metagenomic biomarker discovery and visualization, utilizing the Kruskal-Wallis test, Wilcoxon Rank-Sum test, and Linear Discriminant Analysis. R/Bioconductor provides a large collection of tools for metagenomic data analysis but has lacked an implementation of this widely-used algorithm, hindering benchmarking against other tools and incorporation into R workflows. We present the lefser package to provide comparable functionality within the R/Bioconductor ecosystem of statistical analysis tools, with improvements to the original algorithm for performance, accuracy, and reproducibility.
View Article and Find Full Text PDFBraz J Microbiol
September 2024
P. G. Department of Applied and Interdisciplinary Sciences, Sardar Patel University, V. V. Nagar, Gujarat, 388 120, India.
J Glob Antimicrob Resist
December 2024
Laboratoire de Bactériologie-Hygiène Hospitalière, CHU Grenoble Alpes, Grenoble, France; Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, CEA, IBS, Grenoble, France. Electronic address:
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