Best Engineering Software for R

Compare the Top Engineering Software that integrates with R as of October 2025

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This a list of Engineering software that integrates with R. Use the filters on the left to add additional filters for products that have integrations with R. View the products that work with R in the table below.

What is Engineering Software for R?

Engineering software is software used by engineers to design, analyze and manufacture various products. It includes a wide range of applications such as CAD/CAE software, analysis tools, optimization tools, and programming tools. Engineering software can be used for a variety of tasks such as designing mechanical parts, analyzing structural stability, simulating system performance, and optimizing product designs. These applications enable engineers to optimize their designs for cost reduction and increased efficiency. Compare and read user reviews of the best Engineering software for R currently available using the table below. This list is updated regularly.

1

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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2

BioTuring Browser

BioTuring Browser

Explore hundreds of curated single-cell transcriptome datasets, along with your own data, through interactive visualizations and analytics. The software also supports multimodal omics, CITE-seq, TCR-seq, and spatial transcriptomic. Interactively explore the world's largest single-cell expression database. Access and query insights from a single-cell database of millions of cells, fully annotated with cell type labels and experimental metadata. Not just creating a gateway to published works, BioTuring Browser is an end-to-end solution for your own single-cell data. Import your fastq files, count matrices, Seurat, or Scanpy objects, and reveal the biological stories inside them. Get a rich package of visualizations and analyses in an intuitive interface, making insight mining from any curated or in-house single-cell dataset become such a breeze. Import single-cell CRISPR screening or Perturb-seq data, and query guide RNA sequences.

Starting Price: Free

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3

XetaBase

Zetta Genomics

The unique XetaBase platform simplifies tertiary analysis, aggregating, indexing, and enriching secondary genomic data, enabling continual re-interpretation to unlock research and clinical insight. XetaBase accelerates data management and the cost-effective application of genomic data in the lab and clinic. XetaBase encompasses genomic scale, the greater the volume and complexity, the greater the insight and outcomes. XetaBase is a genomic-native technology, built on the open-source, OpenCB software platform to meet the scale, speed, and re-interpretation demands of genomic medicine. Zetta Genomics delivers genomic data management fit for the precision medicine age. XetaBase is a completely novel solution to the challenges of genomic data. It sweeps away obsolete flat file approaches to bring meaningful and actionable genomic data into the lab and the clinic. XetaBase empowers continual re-interpretation while scaling seamlessly as databases grow to encompass genome sequences.

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4

CZ CELLxGENE Discover

CZ CELLxGENE

Select two custom cell groups based on metadata to find their top differentially expressed genes. Leverage millions of cells from the integrated CZ CELLxGENE corpus for powerful analysis. Execute interactive analyses on a dataset to explore how patterns of gene expression are determined by spatial, environmental, and genetic factors using an interactive speed no-code UI. Understand published datasets or use them as a launchpad to identify new cell sub-types and states. Census provides access to any custom slice of standardized cell data available on CZ CELLxGENE Discover in R and Python. Explore an interactive encyclopedia of 700+ cell types that provides detailed definitions, marker genes, lineage, and relevant datasets in one place. Browse and download hundreds of standardized data collections and 1,000+ datasets characterizing the functionality of healthy mouse and human tissues.

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