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Flow

Bioinformatics software for analyzing and visualizing multiomic data, supporting RNA-Seq, single-cell, spatial transcriptomics, and more.

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, robust statistical algorithms, and information-rich visualizations, enabling researchers of all skill levels to confidently analyze their data.

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: Achieve reliable results using industry-standard statistical methods.
  • Interactive Visualizations: Explore data with detailed, publication-ready visualizations.

Partek Flow supports both on-premises and cloud-based formats and is compatible with microarray and sequencing technologies. It allows for the exploration of complex biological relationships and pathways, aiding in the discovery of meaningful biological insights.

The software provides efficient sample tracking and workflow management for genomics labs, easy sequencing run management, and a comprehensive bioinformatics environment for secure and efficient sequencing operations. It also offers a scalable bioinformatics platform for seamless sequencer integration and flexible workflows.

Partek Flow is available in different editions, including Lab and Enterprise, with options for Illumina-hosted or customer-hosted installations. Each edition offers tools for various applications, with additional add-on tools available for purchase.

Meta

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