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What is ruffus?

Ruffus is a Python library tailored for building computation pipelines, celebrated for its open-source nature, robustness, and ease of use, which makes it especially favored in scientific and bioinformatics applications. This tool facilitates the automation of scientific and analytical processes with minimal complexity, efficiently handling both simple and highly intricate workflows that may pose challenges for conventional tools like make or scons. Rather than relying on intricate tricks or pre-processing methods, it adopts a clear and lightweight syntax that emphasizes functionality. Available under the permissive MIT free software license, Ruffus can be utilized freely and integrated into proprietary software as well. For best results, users are encouraged to run their pipelines in a designated “working” directory, separate from their original datasets, to ensure organization and efficiency. Serving as a flexible Python module for creating computational workflows, Ruffus requires Python version 2.6 or newer, or 3.0 and later, which guarantees its functionality across diverse computing environments. Its straightforward design and high efficacy render it an indispensable asset for researchers aiming to advance their data processing efficiencies while keeping their workflow management simple and effective.

What is Illumina Connected Analytics?

Effectively manage, store, and collaborate on multi-omic datasets with ease. The Illumina Connected Analytics platform provides a secure environment for genomic data, enabling the operationalization of informatics and the extraction of valuable scientific insights. Users have the convenience of importing, creating, and modifying workflows using tools like CWL and Nextflow. The platform integrates DRAGEN bioinformatics pipelines, which enhance data processing capabilities. You can securely organize your data within a protected workspace that allows for global sharing while adhering to compliance standards. Retain your data on your own cloud infrastructure while taking advantage of our powerful platform. A versatile analysis environment, including JupyterLab Notebooks, is available for visualizing and interpreting your data effectively. With a scalable data warehouse, you can aggregate, query, and analyze both sample and population data, adapting to your growing needs. By constructing, validating, automating, and deploying informatics pipelines efficiently, you can significantly reduce the time required for genomic data analysis, which is crucial when rapid results are necessary. Additionally, the platform offers extensive profiling capabilities to discover novel drug targets and pinpoint biomarkers for drug response. Lastly, you can seamlessly integrate data from Illumina sequencing systems, ensuring a smooth and efficient workflow experience while optimizing your research outcomes. This comprehensive approach not only enhances productivity but also fosters collaboration among researchers.

Media

Media

Integrations Supported

Amazon S3
Docker
Illumina DRAGEN Secondary Analysis
JupyterLab
Nextflow
Python

Integrations Supported

Amazon S3
Docker
Illumina DRAGEN Secondary Analysis
JupyterLab
Nextflow
Python

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ruffus

Company Website

www.ruffus.org.uk

Company Facts

Organization Name

Illumina

Company Location

United States

Company Website

www.illumina.com/products/by-type/informatics-products/connected-analytics.html

Categories and Features

Categories and Features

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