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Maximum Discovery

Use Arima’s proven HiC+ technology to generate high-quality data from clinically relevant samples

Depth Without the Depth

Superior sensitivity compared to WGS with proximity-linked reads

Lower Investment

Leverages well-established, short-read NGS technologies; so no need for specialized optical genome mapping or long-read equipment

Generate Comprehensive Insights

Generate dependable results from FFPE tissue samples to detect both coding and non-coding structural variants in this hard-to-use sample type. Learn more about our structural genomics application.

Genome wide HiC_3D Genome Structure_Image

FFPE Sample Results are Highly Correlated to Frozen Tissues. Matched frozen and FFPE tissue of K562 cell cultures were processed with the Arima-HiC+ and Arima-HiC+ FFPE kits, respectively. Libraries were generated following Arima protocols and sequenced using Illumina next generation sequencing (57M and 27M reads were generated, respectively). Representative data for Chromosome 2 at 500 Mb are shown in a. Hi-C contact heat map (500Mb resolution) and b. correlation plot of the normalized Hi-C counts per bin for frozen versus FFPE samples showing a high correlation (r=0.987).

Arima SV Detection Assay Workflow

An end-to-end solution to take you from sample to insights.

Sample Prep

Arima-HiC+ / Arima-HiC+ FFPE Chemistry

Works with cells, liquid biopsy, fresh/frozen tissue and formalin-fixed, paraffin embedded (FFPE) tissue.

Library Prep

Arima Library Prep


Next Generation Sequencing

2 x 150 paired-end reads
Tested on Illumina, Element and Singular NGS platforms.

Data Analysis

Arima Bioinformatics Platform

Leverage the Arima SV QC and Deep Sequencing pipelines.
Compatible with 50–500 million PE reads / clusters. We recommend at least 100M reads.

Matija Snuderl, MD

Director of Molecular Pathology and Diagnostics, NYU Langone Medical Center
“Using Arima Hi-C technology and the new FFPE sample preparation method and bioinformatics tools we’ve been widely successful in detecting structural variants in a variety of tumor samples. We are hopeful that additional insights gained with this approach will lead to improved understanding of disease mechanisms and, ultimately, the development of new therapeutic options for people with cancer.”

Explore Our Resources

Learn more about how you can use Arima HiC+ Kits and Workflows in your research:

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