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Flow

User-friendly software for analyzing and visualizing multiomic data, supporting various sequencing and microarray technologies.

Solution by Partek
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Overview

Partek Flow software is designed for the visual analysis of next-generation sequencing and large-scale multiomic data. It features an intuitive interface that allows researchers of all skill levels to confidently analyze their data using robust statistical algorithms and information-rich visualizations.

The software supports a wide range of applications, including bulk RNA-Seq, single-cell analysis, spatial transcriptomics, ChIP-Seq and ATAC-Seq, DNA-Seq, metagenomics, and microarray data. It is compatible with scalable DRAGEN secondary analysis and offers flexible installation options to meet the needs of individual users, core laboratories, and large enterprises.

Key Features

  • Intuitive: Analyze multiomic data sets with user-friendly tools, requiring no advanced bioinformatics skills.
  • Powerful Statistics: Utilize industry-standard statistical methods to attain reliable results.
  • Interactive Visualizations: Explore data with publication-ready visualizations that are rich in information.

Partek Flow can be deployed on-premises or in the cloud, supporting technologies such as microarray and sequencing. It facilitates the exploration of complex biological relationships and pathways, aiding in the discovery of meaningful biological insights.

The software offers efficient sample tracking and workflow management for genomics labs, easy sequencing run management, and a secure bioinformatics environment for data storage and analysis. It integrates seamlessly with sequencers and provides flexible workflows for comprehensive NGS data analysis.

Subscription options include Lab and Enterprise Editions, with features like RNA-Seq, ChIP-Seq/ATAC-Seq, DNA-Seq, metagenomics, and microarray analysis. Additional add-ons for single-cell and spatial analysis, as well as pathway analysis, are available. The software supports both Illumina-hosted and customer-hosted environments, with options for additional storage and user management features.

Meta

Category
Genomic Data Analysis
Field(s)
Omics & Data Analysis
Target user(s)
Bioinformatician / Data Scientist
Tag(s)
Genomics / NGS Analysis