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Dolomite Bio and Partek Collaborate on Single Cell Analysis Pipeline for Nadia Instrument

Dolomite Bio and Partek Collaborate on Single Cell Analysis Pipeline for Nadia Instrument content piece image
Dolomite Bio's Nadia Instrument
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Dolomite Bio, a leading provider of high throughput single cell technology, and Partek Incorporated, a recognized leader in the development of powerful genomic data analysis tools – have announced a collaboration to combine Partek’s single cell data analysis capabilities with Dolomite Bio’s microfluidic droplet-based single cell technology.

Single cell data analysis enables researchers to gain useful insights into the diversity and state of single cells in a particular sample, which is fundamental for research into many diseases and immunity. However, analyzing single cell data can be challenging without prior advanced bioinformatics skills or in-house capabilities. To solve this challenge, Dolomite Bio and Partek Incorporated are collaborating on the development of an analysis pipeline in Partek® Flow® analysis software which will allow researchers of all backgrounds to easily analyze data and gain unprecedented insights into the expression patterns of single cells, using data generated with Dolomite Bio’s Nadia Instrument.

“Partek Flow is a powerful start-to-finish solution for analyzing genomic data, and delivers the same tools used by bioinformaticians in an easy-to-use and intuitive user interface to make genomic data analysis accessible to all researchers,” said DJ Meyer, Chief Operating Officer for Partek. “Using its single cell toolkit, we’re thrilled that Nadia users will be empowered to explore cell populations, as well as perform flexible differential expression and pathway analyses,” Meyer stated.

Heike Fiegler, Vice President of Biology Products for Dolomite Bio, commented on the collaboration: “We are delighted to collaborate with Partek to offer our Nadia customers a single cell data analysis solution. With the data analysis expertise of Partek, Nadia users will now be able to effortlessly analyze their single cell data without any prior bioinformatics knowledge.”