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Description

Manage, store, and collaborate on multi-omic datasets effectively. The Illumina Connected Analytics platform serves as a secure environment for genomic data, facilitating the operationalization of informatics and the extraction of scientific insights. Users can effortlessly import, construct, and modify workflows utilizing tools such as CWL and Nextflow. The platform also incorporates DRAGEN bioinformatics pipelines for enhanced data processing. Securely organize your data within a protected workspace, enabling global sharing that adheres to compliance standards. Retain your data within your own cloud infrastructure while leveraging our robust platform. Utilize a versatile analysis environment, featuring JupyterLab Notebooks, to visualize and interpret your data. Aggregate, query, and analyze both sample and population data through a scalable data warehouse, which can adapt to your growing needs. Enhance your analysis operations by constructing, validating, automating, and deploying informatics pipelines with ease. This efficiency can significantly decrease the time needed for genomic data analysis, which is vital when rapid results are essential. Furthermore, the platform supports comprehensive profiling to uncover novel drug targets and identify biomarkers for drug response. Lastly, seamlessly integrate data from Illumina sequencing systems for a streamlined workflow experience.

Description

Ruffus is a Python library designed for creating computation pipelines, known for being open-source, robust, and user-friendly, making it particularly popular in scientific and bioinformatics fields. This tool streamlines the automation of scientific and analytical tasks with minimal hassle and effort, accommodating both simple and extremely complex pipelines that might confuse traditional tools like make or scons. It embraces a straightforward approach without relying on "clever magic" or pre-processing, focusing instead on a lightweight syntax that aims to excel in its specific function. Under the permissive MIT free software license, Ruffus can be freely utilized and incorporated, even in proprietary applications. For optimal performance, it is advisable to execute your pipeline in a separate “working” directory, distinct from your original data. Ruffus serves as a versatile Python module for constructing computational workflows and requires a Python version of 2.6 or newer, or 3.0 and above, ensuring compatibility across various environments. Moreover, its simplicity and effectiveness make it a valuable tool for researchers looking to enhance their data processing capabilities.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon S3 Yes 
Docker Yes 
Illumina DRAGEN Secondary Analysis Yes 
JupyterLab Yes 
Nextflow Yes 
Python No 

Integrations

Amazon S3 No 
Docker No 
Illumina DRAGEN Secondary Analysis No 
JupyterLab No 
Nextflow No 
Python Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Illumina

Country

United States

Website

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

Vendor Details

Company Name

ruffus

Website

www.ruffus.org.uk

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