Best Genomics Data Analysis Software for Docker
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Compare the Top Genomics Data Analysis Software that integrates with Docker as of July 2025
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This a list of Genomics Data Analysis software that integrates with Docker. Use the filters on the left to add additional filters for products that have integrations with Docker. View the products that work with Docker in the table below.
What is Genomics Data Analysis Software for Docker?
Genomics data analysis software helps researchers and scientists analyze and interpret large-scale genomic data, enabling insights into genetic variations, mutations, and biological functions. It provides tools for processing raw genomic sequences, aligning them to reference genomes, and identifying significant patterns or mutations. The software often includes features like data visualization, statistical analysis, and integration with other biological datasets to support comprehensive research. By automating complex analyses, genomics data analysis software accelerates research workflows and improves the accuracy of genetic insights. Ultimately, it advances scientific discovery and personalized medicine by enabling a deeper understanding of the human genome and other organisms. Compare and read user reviews of the best Genomics Data Analysis software for Docker currently available using the table below. This list is updated regularly.
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Genome Analysis Toolkit (GATK)
Broad Institute
Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size. The GATK is the industry standard for identifying SNPs and indels in germline DNA and RNAseq data. Its scope is now expanding to include somatic short variant calling and to tackle copy number (CNV) and structural variation (SV). In addition to the variant callers themselves, the GATK also includes many utilities to perform related tasks such as processing and quality control of high-throughput sequencing data and bundles the popular Picard toolkit. These tools were primarily designed to process exomes and whole genomes generated with Illumina sequencing technology, but they can be adapted to handle a variety of other technologies and experimental designs.Starting Price: Free -
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Bioconductor
Bioconductor
The Bioconductor project aims to develop and share open source software for precise and repeatable analysis of biological data. We foster an inclusive and collaborative community of developers and data scientists. Resources to maximize the potential of Bioconductor. From basic functionalities to advanced features, our tutorials, guides, and documentation have you covered. Bioconductor uses the R statistical programming language and is open source and open development. It has two releases each year and an active user community. Bioconductor provides Docker images for every release and provides support for Bioconductor use in AnVIL. Founded in 2001, Bioconductor is an open-source software project widely used in bioinformatics and biomedical research. It hosts over 2,000 R packages contributed by over 1,000 developers, with over 40 million downloads per year. Bioconductor has been cited in more than 60,000 scientific publications.Starting Price: Free -
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Illumina Connected Analytics
Illumina
Store, archive, manage, and collaborate on multi-omic datasets. Illumina Connected Analytics is a secure genomic data platform to operationalize informatics and drive scientific insights. Easily import, build, and edit workflows with tools like CWL and Nextflow. Leverage DRAGEN bioinformatics pipelines. Organize data in a secure workspace and share it globally in a compliant manner. Keep your data in your cloud environment while using our platform. Visualize and interpret your data with a flexible analysis environment, including JupyterLab Notebooks. Aggregate, query, and analyze sample and population data in a scalable data warehouse. Scale analysis operations by building, validating, automating, and deploying informatics pipelines. Reduce the time required to analyze genomic data, when swift results can be a critical factor. Enable comprehensive profiling to identify novel drug targets and drug response biomarkers. Flow data seamlessly from Illumina sequencing systems.
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